{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-title"
    ]
   },
   "source": [
    "# Implementing a Neural Network\n",
    "In this exercise we will develop a neural network with fully-connected layers to perform classification, and test it out on the CIFAR-10 dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "is_executing": false
    },
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [],
   "source": [
    "# A bit of setup\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from cs231n.classifiers.neural_net import TwoLayerNet\n",
    "\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# for auto-reloading external modules\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "def rel_error(x, y):\n",
    "    \"\"\" returns relative error \"\"\"\n",
    "    return np.max(np.abs(x - y) / (np.maximum(1e-8, np.abs(x) + np.abs(y))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "source": [
    "We will use the class `TwoLayerNet` in the file `cs231n/classifiers/neural_net.py` to represent instances of our network. The network parameters are stored in the instance variable `self.params` where keys are string parameter names and values are numpy arrays. Below, we initialize toy data and a toy model that we will use to develop your implementation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [],
   "source": [
    "# Create a small net and some toy data to check your implementations.\n",
    "# Note that we set the random seed for repeatable experiments.\n",
    "\n",
    "input_size = 4\n",
    "hidden_size = 10\n",
    "num_classes = 3\n",
    "num_inputs = 5\n",
    "\n",
    "def init_toy_model():\n",
    "    np.random.seed(0)\n",
    "    return TwoLayerNet(input_size, hidden_size, num_classes, std=1e-1)\n",
    "\n",
    "def init_toy_data():\n",
    "    np.random.seed(1)\n",
    "    X = 10 * np.random.randn(num_inputs, input_size)\n",
    "    y = np.array([0, 1, 2, 2, 1])\n",
    "    return X, y\n",
    "\n",
    "net = init_toy_model()\n",
    "X, y = init_toy_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Forward pass: compute scores\n",
    "Open the file `cs231n/classifiers/neural_net.py` and look at the method `TwoLayerNet.loss`. This function is very similar to the loss functions you have written for the SVM and Softmax exercises: It takes the data and weights and computes the class scores, the loss, and the gradients on the parameters. \n",
    "\n",
    "Implement the first part of the forward pass which uses the weights and biases to compute the scores for all inputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your scores:\n",
      "[[-0.81233741 -1.27654624 -0.70335995]\n",
      " [-0.17129677 -1.18803311 -0.47310444]\n",
      " [-0.51590475 -1.01354314 -0.8504215 ]\n",
      " [-0.15419291 -0.48629638 -0.52901952]\n",
      " [-0.00618733 -0.12435261 -0.15226949]]\n",
      "\n",
      "correct scores:\n",
      "[[-0.81233741 -1.27654624 -0.70335995]\n",
      " [-0.17129677 -1.18803311 -0.47310444]\n",
      " [-0.51590475 -1.01354314 -0.8504215 ]\n",
      " [-0.15419291 -0.48629638 -0.52901952]\n",
      " [-0.00618733 -0.12435261 -0.15226949]]\n",
      "\n",
      "Difference between your scores and correct scores:\n",
      "3.680272087688147e-08\n"
     ]
    }
   ],
   "source": [
    "scores = net.loss(X)\n",
    "print('Your scores:')\n",
    "print(scores)\n",
    "print()\n",
    "print('correct scores:')\n",
    "correct_scores = np.asarray([\n",
    "  [-0.81233741, -1.27654624, -0.70335995],\n",
    "  [-0.17129677, -1.18803311, -0.47310444],\n",
    "  [-0.51590475, -1.01354314, -0.8504215 ],\n",
    "  [-0.15419291, -0.48629638, -0.52901952],\n",
    "  [-0.00618733, -0.12435261, -0.15226949]])\n",
    "print(correct_scores)\n",
    "print()\n",
    "\n",
    "# The difference should be very small. We get < 1e-7\n",
    "print('Difference between your scores and correct scores:')\n",
    "print(np.sum(np.abs(scores - correct_scores)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Forward pass: compute loss\n",
    "In the same function, implement the second part that computes the data and regularization loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Difference between your loss and correct loss:\n",
      "1.7985612998927536e-13\n"
     ]
    }
   ],
   "source": [
    "loss, _ = net.loss(X, y, reg=0.1)\n",
    "correct_loss = 1.30378789133\n",
    "\n",
    "# should be very small, we get < 1e-12\n",
    "print('Difference between your loss and correct loss:')\n",
    "print(np.sum(np.abs(loss - correct_loss)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Backward pass\n",
    "Implement the rest of the function. This will compute the gradient of the loss with respect to the variables `W1`, `b1`, `W2`, and `b2`. Now that you (hopefully!) have a correctly implemented forward pass, you can debug your backward pass using a numeric gradient check:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b2 max relative error: 2.107308e-10\n",
      "W2 max relative error: 3.440708e-09\n",
      "W1 max relative error: 3.561318e-09\n",
      "b1 max relative error: 1.555470e-09\n"
     ]
    }
   ],
   "source": [
    "from cs231n.gradient_check import eval_numerical_gradient\n",
    "\n",
    "# Use numeric gradient checking to check your implementation of the backward pass.\n",
    "# If your implementation is correct, the difference between the numeric and\n",
    "# analytic gradients should be less than 1e-8 for each of W1, W2, b1, and b2.\n",
    "\n",
    "loss, grads = net.loss(X, y, reg=0.05)\n",
    "\n",
    "# these should all be less than 1e-8 or so\n",
    "for param_name in grads:\n",
    "    f = lambda W: net.loss(X, y, reg=0.05)[0]\n",
    "    param_grad_num = eval_numerical_gradient(f, net.params[param_name], verbose=False)\n",
    "    print('%s max relative error: %e' % (param_name, rel_error(param_grad_num, grads[param_name])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train the network\n",
    "To train the network we will use stochastic gradient descent (SGD), similar to the SVM and Softmax classifiers. Look at the function `TwoLayerNet.train` and fill in the missing sections to implement the training procedure. This should be very similar to the training procedure you used for the SVM and Softmax classifiers. You will also have to implement `TwoLayerNet.predict`, as the training process periodically performs prediction to keep track of accuracy over time while the network trains.\n",
    "\n",
    "Once you have implemented the method, run the code below to train a two-layer network on toy data. You should achieve a training loss less than 0.02."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final training loss:  0.017143643532923747\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "net = init_toy_model()\n",
    "stats = net.train(X, y, X, y,\n",
    "            learning_rate=1e-1, reg=5e-6,\n",
    "            num_iters=100, verbose=False)\n",
    "\n",
    "print('Final training loss: ', stats['loss_history'][-1])\n",
    "\n",
    "# plot the loss history\n",
    "plt.plot(stats['loss_history'])\n",
    "plt.xlabel('iteration')\n",
    "plt.ylabel('training loss')\n",
    "plt.title('Training Loss history')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the data\n",
    "Now that you have implemented a two-layer network that passes gradient checks and works on toy data, it's time to load up our favorite CIFAR-10 data so we can use it to train a classifier on a real dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  (49000, 3072)\n",
      "Train labels shape:  (49000,)\n",
      "Validation data shape:  (1000, 3072)\n",
      "Validation labels shape:  (1000,)\n",
      "Test data shape:  (1000, 3072)\n",
      "Test labels shape:  (1000,)\n"
     ]
    }
   ],
   "source": [
    "from cs231n.data_utils import load_CIFAR10\n",
    "\n",
    "def get_CIFAR10_data(num_training=49000, num_validation=1000, num_test=1000):\n",
    "    \"\"\"\n",
    "    Load the CIFAR-10 dataset from disk and perform preprocessing to prepare\n",
    "    it for the two-layer neural net classifier. These are the same steps as\n",
    "    we used for the SVM, but condensed to a single function.  \n",
    "    \"\"\"\n",
    "    # Load the raw CIFAR-10 data\n",
    "    cifar10_dir = 'cs231n/datasets/cifar-10-batches-py'\n",
    "    \n",
    "    # Cleaning up variables to prevent loading data multiple times (which may cause memory issue)\n",
    "    try:\n",
    "       del X_train, y_train\n",
    "       del X_test, y_test\n",
    "       print('Clear previously loaded data.')\n",
    "    except:\n",
    "       pass\n",
    "\n",
    "    X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir)\n",
    "        \n",
    "    # Subsample the data\n",
    "    mask = list(range(num_training, num_training + num_validation))\n",
    "    X_val = X_train[mask]\n",
    "    y_val = y_train[mask]\n",
    "    mask = list(range(num_training))\n",
    "    X_train = X_train[mask]\n",
    "    y_train = y_train[mask]\n",
    "    mask = list(range(num_test))\n",
    "    X_test = X_test[mask]\n",
    "    y_test = y_test[mask]\n",
    "\n",
    "    # Normalize the data: subtract the mean image\n",
    "    mean_image = np.mean(X_train, axis=0)\n",
    "    X_train -= mean_image\n",
    "    X_val -= mean_image\n",
    "    X_test -= mean_image\n",
    "\n",
    "    # Reshape data to rows\n",
    "    X_train = X_train.reshape(num_training, -1)\n",
    "    X_val = X_val.reshape(num_validation, -1)\n",
    "    X_test = X_test.reshape(num_test, -1)\n",
    "\n",
    "    return X_train, y_train, X_val, y_val, X_test, y_test\n",
    "\n",
    "\n",
    "# Invoke the above function to get our data.\n",
    "X_train, y_train, X_val, y_val, X_test, y_test = get_CIFAR10_data()\n",
    "print('Train data shape: ', X_train.shape)\n",
    "print('Train labels shape: ', y_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Validation labels shape: ', y_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train a network\n",
    "To train our network we will use SGD. In addition, we will adjust the learning rate with an exponential learning rate schedule as optimization proceeds; after each epoch, we will reduce the learning rate by multiplying it by a decay rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": [
     "code"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1000: loss 2.302762\n",
      "iteration 100 / 1000: loss 2.302358\n",
      "iteration 200 / 1000: loss 2.297404\n",
      "iteration 300 / 1000: loss 2.258897\n",
      "iteration 400 / 1000: loss 2.202975\n",
      "iteration 500 / 1000: loss 2.116816\n",
      "iteration 600 / 1000: loss 2.049789\n",
      "iteration 700 / 1000: loss 1.985711\n",
      "iteration 800 / 1000: loss 2.003726\n",
      "iteration 900 / 1000: loss 1.948076\n",
      "Validation accuracy:  0.287\n"
     ]
    }
   ],
   "source": [
    "input_size = 32 * 32 * 3\n",
    "hidden_size = 50\n",
    "num_classes = 10\n",
    "net = TwoLayerNet(input_size, hidden_size, num_classes)\n",
    "\n",
    "# Train the network\n",
    "stats = net.train(X_train, y_train, X_val, y_val,\n",
    "            num_iters=1000, batch_size=200,\n",
    "            learning_rate=1e-4, learning_rate_decay=0.95,\n",
    "            reg=0.25, verbose=True)\n",
    "\n",
    "# Predict on the validation set\n",
    "val_acc = (net.predict(X_val) == y_val).mean()\n",
    "print('Validation accuracy: ', val_acc)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Debug the training\n",
    "With the default parameters we provided above, you should get a validation accuracy of about 0.29 on the validation set. This isn't very good.\n",
    "\n",
    "One strategy for getting insight into what's wrong is to plot the loss function and the accuracies on the training and validation sets during optimization.\n",
    "\n",
    "Another strategy is to visualize the weights that were learned in the first layer of the network. In most neural networks trained on visual data, the first layer weights typically show some visible structure when visualized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the loss function and train / validation accuracies\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(stats['loss_history'])\n",
    "plt.title('Loss history')\n",
    "plt.xlabel('Iteration')\n",
    "plt.ylabel('Loss')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.plot(stats['train_acc_history'], label='train')\n",
    "plt.plot(stats['val_acc_history'], label='val')\n",
    "plt.title('Classification accuracy history')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Classification accuracy')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from cs231n.vis_utils import visualize_grid\n",
    "\n",
    "# Visualize the weights of the network\n",
    "\n",
    "def show_net_weights(net):\n",
    "    W1 = net.params['W1']\n",
    "    W1 = W1.reshape(32, 32, 3, -1).transpose(3, 0, 1, 2)\n",
    "    plt.imshow(visualize_grid(W1, padding=3).astype('uint8'))\n",
    "    plt.gca().axis('off')\n",
    "    plt.show()\n",
    "\n",
    "show_net_weights(net)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tune your hyperparameters\n",
    "\n",
    "**What's wrong?**. Looking at the visualizations above, we see that the loss is decreasing more or less linearly, which seems to suggest that the learning rate may be too low. Moreover, there is no gap between the training and validation accuracy, suggesting that the model we used has low capacity, and that we should increase its size. On the other hand, with a very large model we would expect to see more overfitting, which would manifest itself as a very large gap between the training and validation accuracy.\n",
    "\n",
    "**Tuning**. Tuning the hyperparameters and developing intuition for how they affect the final performance is a large part of using Neural Networks, so we want you to get a lot of practice. Below, you should experiment with different values of the various hyperparameters, including hidden layer size, learning rate, numer of training epochs, and regularization strength. You might also consider tuning the learning rate decay, but you should be able to get good performance using the default value.\n",
    "\n",
    "**Approximate results**. You should be aim to achieve a classification accuracy of greater than 48% on the validation set. Our best network gets over 52% on the validation set.\n",
    "\n",
    "**Experiment**: You goal in this exercise is to get as good of a result on CIFAR-10 as you can (52% could serve as a reference), with a fully-connected Neural Network. Feel free implement your own techniques (e.g. PCA to reduce dimensionality, or adding dropout, or adding features to the solver, etc.)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "**Explain your hyperparameter tuning process below.**\n",
    "\n",
    "$\\color{blue}{\\textit Your Answer:}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "tags": [
     "code"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Validation accuracy: 0.509000 h_size: 125 learning rate: 0.001100 reg: 0.750000\n"
     ]
    }
   ],
   "source": [
    "best_net = None # store the best model into this \n",
    "\n",
    "#################################################################################\n",
    "# TODO: Tune hyperparameters using the validation set. Store your best trained  #\n",
    "# model in best_net.                                                            #\n",
    "#                                                                               #\n",
    "# To help debug your network, it may help to use visualizations similar to the  #\n",
    "# ones we used above; these visualizations will have significant qualitative    #\n",
    "# differences from the ones we saw above for the poorly tuned network.          #\n",
    "#                                                                               #\n",
    "# Tweaking hyperparameters by hand can be fun, but you might find it useful to  #\n",
    "# write code to sweep through possible combinations of hyperparameters          #\n",
    "# automatically like we did on the previous exercises.                          #\n",
    "#################################################################################\n",
    "# *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "best_net=None\n",
    "best_acc=0.0\n",
    "best={}\n",
    "hidden_size = [75, 100, 125]\n",
    "learning_rates = np.array([0.7, 0.8, 0.9, 1, 1.1])*1e-3\n",
    "regularization_strengths = [0.75, 1, 1.25]\n",
    "\n",
    "for h_size in hidden_size:\n",
    "    for rate in learning_rates:\n",
    "        for reg in regularization_strengths:\n",
    "            net=TwoLayerNet(input_size,h_size,num_classes)\n",
    "            \n",
    "            stats = net.train(X_train, y_train, X_val, y_val,num_iters=1500, batch_size=200,\n",
    "                learning_rate=rate, learning_rate_decay=0.95,reg=reg, verbose=False)\n",
    "            val_acc = (net.predict(X_val) == y_val).mean()\n",
    "            if val_acc>best_acc:\n",
    "                best_acc=val_acc\n",
    "                best_net=net\n",
    "                best['reg']=reg\n",
    "                best['rate']=rate\n",
    "                best['h_size']=h_size\n",
    "\n",
    "print('Best Validation accuracy: %f h_size: %d learning rate: %f reg: %f' %(best_acc,best['h_size'],best['rate'],best['reg']))\n",
    "\n",
    "# *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MSpLG/pT28Tl6dp29o0dY9kUAn8xmuAfvs/3YIysWmBRDMt0INZ7g1de/wLvvfJeFcg1ZzzC2WkyFgI4Ux1IGzNQIdXCRgTW3zihqDZqTGWIkkFEjPmodkqjWKWe/ykhv8cacSnsYEBUyTDu7zKPS/fr3OW8OefWrP/ec2+WVTR52jyjqeVLxBI86U84bNpNRxM4HDRYWspzcn3H5SoHTj35IXovzSj5PxpVQzN5zO+2zBgYJhrsW1zcu0R4HaOOAsOcwPPKZm6osZj/HK5Us9vSMjfk12t0hhVgew5W4/973ATg+NNFSCywZCfY+fEShpNAYdymtSLz5Vo3+4Yjm0zZ7SExTOqOpwG/8we9wp1ojl48zI/uJMfipEILISXDYDJATIsk5g3EjwWZtnkTRofv4lMW1e7z93i7phTUsSafZaLJy6S28oIWil/CUPABXLpWwzjoMT3Sul9bYPevhpAVyV+t0wySdlMxRT2XWFqjHbhAP9wlnJldXL7O/+02E8IVsPt5vUKmnWS553FxOUS/MM5BMhEDlWJ7R7j+mKiU4Omxy7fo1JFMkOUvw0aHLk52953bGU5eW18d3LfJaiDSysawZDqCk5jg7H3B3VedsYCGTYjxsU1AEUpUq+VDGFS/SzAfbH3Hz0lu41oCz/iMkr0DfLKCGEZEPnV6PWl7HSrj0z7v0AgU5JaNksvSGY85PLxph9y4vMbE0nj57hqqniSXjVC4vcPZ4n48/+gZ/+rWb9FwPRqf4xgwPgc3FFGMKXM5AfXmT3/4RN7PjsrwZ0jxq8OatBeruhMPhMaWri7S8Lu+MdljLXMNsjlgslYmCKuI4y+npmOFERjMuMoKtZpNiYpOFpTJX0nGOfm+Hjde+gnnyhL2zPZYLdSI1SaszQoj59KcCiXqF+8+eUs67WIcX52YpIqW0xvUrKQ6Ox7RSNrVSjnfOd/lg9j3WlxIEh30Uu0V9M82SluZf/L1f4SfiecQ2KNGLYDk8+piJPyTXm5HS1/ji+hKuEqHHL3FtsYBlN8nJJs8en7NgrNF48G2uXu9gxmscPnzRI3C8Kc3WPiuxJUS7gDLxeOX2dR67CT7z+RVODs5JWxKzqEBSSzNp7nP46JBLr9a5v/MDqisX53/r8gbb+w3syYxaOY9VHVLbnGcUHRPhIpWTzKm3GB56JOey7I98pj0JN5UnEHPE9WufGIOfCiF4sHvIRNTIlxPMpWwendRhLomuepx1HN7ZeR+3NcR59wDP9Mihk0zMqBWK9O2Akvij2t7cJ5p4ZObWON55SP3WlxCMIr/+O7/LnX/tP+ZU6NFsP2Mpm2PVUOh1DORShnNzRlSqMj5tPPfJ1w3m1RglL8DefcqlH19mf2JzFnYoewFaLI1qJFgqrhAcjOmedCnWlug2zzg9az+34wYOscEYNa7jeTAwLQTXI+5C4HRo7h5j6oukIpmTgyb1YpZqKQ+mx5yW4HB00cCME0MT0ohBj8L8ZYqGgx6XWaosMWg1qSRrxPMG551tokggZvssLW9w8mCPkpjEqMwBcNDfJiWMMdJZVoH6pasM3CmyZVKRErz9nd/lZ7/yJsHrBY5GAqEg8t633qWiS4wnFgN3/JzbuGPz9MkppXvrSDkdf7zLyvIGTfEIaTnNLXUdsWdwefEOv/dr30DqyyxX6pg9H6k1RYguXvIrayvMX15HHLRRLJ/N9SXY20LybK5duYUQ9jjsi0RiEqUispyROK0qXLIlXC9i5SeX4Jd+CSNVJWjnEWdT0kWFncOHdLN1cpcX+VduJfmd7zxgLTchE9o0Pn5CPVvnS1fvkH92gnZnAWX63nNupaLI/DSJrBg4ko816TF0ZXSly7g/YLq7xeqryySiMesbl7lbeZONXMSj9x/Stl80nY/2HuL2bRSxxf5DgaUbb3Den6AU69z80lusdVs4jSHz9hTfikNMhKNtvvuDd4gKFlF3AMD+O/ucHgTMNoo0Z7sYpWVOYlM25rK0lZCxJHLywRFemCIuXifmvo8eLzI57nL75gaj8+YnxuCnQgjiiTIJbUpehSis8LnPblKKayTjKWaNPqloi+3BFt/98CkpRSaVybKSSVIoJCnnRPbfewjA61/9DEe7Ks3tGaHv0W83KGkJMkmFwcPf5Ds//IhcRkMVl3lnv4ekxLlcyDBr+1y9c4XZCvyvO98GIJdMM95rQEzk/tEeDb/DeSwiXEnSHwwZ9mw6cwbSoYu3ZZFM1TnaHTBflHnjzbf4xju/BsDZ9i7Xb1xCSsaxnIjdZ8/IldLERIVRb8rr80XM+9tcWqtRLSeRQo/bpSJyEHF+0kOVL1L60AfR7LGyUmFoh3QP98jklzma2Nh6jtD2CQ4CvEAlVV9AUGZs3b/P7VoNXUvj9iUAtu4/QVMC3nx1gY5lkZGOUO010sUYxx/vkpmP8eEP36eZTpMoFSnXq3RWqwjYLKST9A/2n5/b/MIShhswJ1v843/0TVbvzRACn6hukPSrPN464K03v8LOwz4Llz/HD/7ZgBQW6XDKndeXOW9dpNDV+XXOT3b5k69fovn293B3pgzjEid7EcuoKKk4A2vAdmPCYmaOoN9kGqis3b3LzpmLY1001MTBQ0ZWg27rjGxZJ4tIfuEmg8jk8e//PSb7x3Q0g1df26R6dY7tBw1uX78OsTi64KCL1nNuzZMur756h3nTxhxmUQYnNO1DLiUXeXJ2zmtfvsqgPWZjyeDo2ffZWI6henXmV17h2daHz+1kLi0w2O/xw68/xNBlnr0fkdndYe3WQx7t/jOawwnV2gKWlOJgb4vG0GcuLuMcm6zcKRCvlOF/f0IYL3F7w+I77QPK9euMey18VeAPD7r83M9/hUXfpPZanpPTKd9/cIQfFMlLcUTGlLMmw9aLac8fhU+FEGx3BiSNCL87hlgc2YeYUaRgZHj0/gnWjoN5bmOMVOTUhHQqQ+90ytRuI/rzzGY2AH3Fw1MDdtunzNfWMLvnPO4O8XM6283HfPatNezWBEk94mR4xBd/4suM9pqImsXUcrFN6YVTwozV8jz9WZ/6xhoxYUghqeBJGWRfYvOVIsIk4tGH30fpZLhtLDDzB9T0El/faz03k8Yn54HmR3h6mrUrt3j2g2+RKeWI5fPkamW2rAmryRKxRI1CUuL1W1cYjALM3n12nhwCsFqqUkjF8J0OSQGEuTVMs4dpW+QW7jATIFMUSapVdlpNznpj5uU0cm/A/LVFdho/GkM6M3RJ5xtPz+maEyqHFvF4yOHBR/SfbXNdW0YaSmy3q3zu+m1GwyFSKoloBfT6p8iq/pxbLD4knU/S3G1wb3WOaettRgOH+tIlEq7Ho70YW7Fzjt+F7bcjklqZw/4Rry0vsPvsjIXlGgCWL7C6kqV99AHLa1nePe2xczygF2qcvv2HrKxWSKfzhJNTTrsBesJisVKl6LZI3nqVmXmREZptj1k3JPuFf5vS1QInDx4jTl0+PDjAOT/kyckEeeM1DseLLC9tcOPLXaLdEXpplfc//D6yHzznJnkas90hJ1qObFqiEuRY2JxDU1TqSbi3keI4oTI9apEwQ8SGxdXrEh89HhHyYvq0454Tz/iYSYXavMH2sIuXSxBETxlbPgXZw2kN+NrDj0klI0r1G0iexsL1Er4oMIoumrP7pw2iaJsbaej4PTQlQePslNm0w/G7P6C33eHerRydwQKH3/s6krbCZNzhT72+zHhyxvLVT54afCqE4I1KksbgAHk4Yc9K8pmNK1yau0ncz3AYjbFiAXpvj8zMp7Qwx+3qPOH4iHEosXppjcfiRf3rTaHr2pTv3YYgZKffoSuLzOcLSF6D+UqKp4NdVjIGxmYWUR7TFWzubsxx1N2lWH4xPjppOpwtqEjJEoXkIYVcgdC0cFohYjzL/DSJrivklz9LoE6YixQKlUt8fDbk7PxFaTD1Uhw2HbJODF3oo2sin795l/PzDqVcjUQ8S6bscPvO5/H6E2KKxrMHE06OTumbJrowBaC6vIEw9HB7XU4H5xyIFnPVNcbdiHHUJirNc9ybspGJMxlP8IYynbxGauRgNkOO2heXPOn3MUctEstXydfSJJUFpmOBS3eucug2yCo6u7ZPvKrywfYHRK7NXCXOXmeXaNZDil6MD01DY+JNSaYEBgfnkIkzHQfETg0qtWX+9c2rHHWHHNs9XvuxOnNCDmvic9IYc3Zwxnz+4iW3bZfR0SHVuSz9qUuYAfuZRc4XiC1pnDpdnj06wO2cYG4dUrh5m0JdJFfaYBBO2P/RjkR6dp/q3Tpbux/gCB5y9RqdRo+1hTQPxyL3yudUpBQiNcxRAbdxSj2/gO2N+eKf+CJGP/6Cm6xj5qrEIhlZ0qhlLrIEKS9TDEb84Lf/OQoh1ew6kpZGcQOOWhkq8xkGkxeTldWCzlR0+fK/9SVCzyY26fGtvQdocp38co7DrYdU5gWE/WOqNz9L6DrYXox6ucTvbW/zxVtfurCzovPut7aopwo86vZZqS4zPo4jhTrB4ySpcJ3+gw6Pjntsrr9GORHHH+8QjdtYiRyRNvnEGPxUCEE8AeZeG8mTyMUEBD+G6CaxnRlDK2A4ClGr89xeWqLb3MUa+yzWUti+hT2ZYnkX6XN3MuF8KnH52hr2oEsitLAnLfaOety5XKbRPUEQ22STcc6aDRLqJXTTRsrH0UWFyH+xWSiJENMiIlUiphSwByfEdB03tCkoKWqxEHPUohYzSMzlwckzHU1REjpR8GKPIKYIBGFAezBEljVE0SAeU5ihMJ4EKBmFcm0ZeypRSRXxI5XHz7a4f3+Ls8mIWmUROGGn2+aVTBozimFFKklDgsmUYTfEUIcMgwnR1OU0nqWcdOkOhzCRWFmtIZBEti6mD/FURKCJTDybTKVIEhmJHLsP3mF15TJxMYEvTNElndHYJplPcNg+xcgbCMcdEvHEc25CCLYwI5vIEyoJYmqVQD7ncMskHhUxlAy6E2MxKxB2XLSEjRUXSBYLaImIUvlipGmk00hdn1AUSKYy2P0j1hbq5D0R2x/Sc4eYoocMVIoGoRyj3Tkir/wUspph9GQIwHI2RtsLyGSySGqacOKSrZbohyZ5vY4fZrAkDdN1EHunOM1DtDDGZq1AKBQ46T1+zm00maHEEwydMbdWVlHHI0LdIwymGFqSMosIdEmoWerLdXZPe/SnMk48xnDw4m6PJzPOOia3PrfMtHFMN2wxX1OZzAYkI0jOx8knepBRcM02tco1OAlJZbJkKmlM94LbaGRyPhUx4i7FIE8lXSFaSvP+0zHnjywivY1fW2Qtp/Do/JyCFyO1sIgz6aFpKo70yZsCnwoh2Ntt4CKBN0WYRuzb30GLhYQtl3i/hSJYzBy4fWORI2PIXE4jVzCwmnscPu6geRcXKlOsMj8VSEoKjhRnYbmK4SWxvDaZQpFFbYxR1/nhDx8gOEm2DnfwhB4ntkVMnaEVXvhUmDMYqgYxX6aWSdM7G1HK63j5JEVZJaPa+K5BMwIh0DkZWjhyxIfnA2bSixRzsVqiZdkQCUyGEw6e7XFtPk1hYZHTiU2s1cVXdR7u/5BUPM/RaY+t4wazMEZvOGSxelHb/eH33iFw1/BGPTx3xOrGm3Rau7jKBMsUeLIf4Qz2SKhZJjUDJYgjmhFTK+Sk3eWkdXGhBoNz5laXWL5WZa835AcfN8nk4ixtznG222esCnQ9g7QikcSnlsnQkY6JNSOUWIp44DznVlIi+pJOo+FRTdYRhAkJL2JBW2Xnoya6aGC1d0hkEzTODU68Pl4yIBsLyNVULOGiJt+dNLmWyvLO977LekzitdXr7H37GY/3ziheu8S4GdAfOiyU69RTFc5mU0rdPM13HzBYTGJPLi55JjmHml9m7GY4mspEsoCtlZmafZJqiVZJIdoaU5sU+Hhvm+rlNzCDGN3GjJQUMZ97sVnYsSweHu4jRSPiM5f+8TmvXq9hGxUCz6e2mSEc5XnwcRcp7LA/dhEzMd47a4D5oqEqpcpcT2tMJ/Bwr4s/n+WV26/SnJyyUFLYNC7R2jEplIvU5uqY0gwlpTJVXVY2syRyF9+otX/GnZUbnPkBcq/LdOCQjRReq9+mO5jRbvX46O1/yfLmPHfuvsroZBdYf6gPAAAgAElEQVS3E0dOFjEnM1zsT4zBT4UQ5NYK5CcW9qhNaa6EMk0wEk8ZTA9ZWl/BPWuhrxposT6fuVMnkdaZ0GOy00UWHFLxi8BbyazTiU5pdbrYwQjXDri5ucx0YNA7Mxm5U4xSntfX30IyTR6cD9FzKRbyacZmBzF6kRoKSoqBO0RI6/imThSrEk+vMRoPeLvfIR31aPYcrt66iW06tGPwdKvB7lQizMw/t7O+vkQ0aDP2BNyGg36pzNQG2UnTjxKcHA3R3FOajsCHH3wD2dUI3JBQE5hfy5KerwPfZNc74SfERe5e+zFm3pTj3gDRk9ioXaOyvkJtf4uktoQiKEw6Q/qeiDj0+NznvsJ3T/cZJC8mIu6kC7MkwviEow+30byQzfJbzNfXSM7OSBpp4j2XOCLPmk/wRnuIcRlDHFCq5rH3nj3ndj44xI1HmH6RO9dXiWZVimqd08455x0BIzpAEiMqZDCW6wwUg2f7H9GwJyyV5pgrVwE4ODzk9pXL/MzVLyAZLu9//TsEaYtiLclbmwbbeFTES8Qln7PpKetr10lmlzBTKwzDFFbsokvf6rfILl/je80dZjOfu/fuIXs+8qhPW03yU3e/ylMe0XUPufPGmyTdM87OT5l6sDxXIGW9aBbObdzj3fOP8cdjHrt9dh9v853tNexYAvJpYmoc73SHWKXK7nuPyOkLlPMiTT+gVlt6bicby+N5HtvHx2SKaaypRelKnV5nSP9sTH2lQjRzuXv9FTw/izW2mOoCJUEkcix882KkmaooqIqHf+SQz1VIhSlOZy5q5GIOFeRRn9sbJRZKOaRxn4SSZCr5TLsmKT1JsfD/gozAcjq0JiaJyZDkoURuNc3WRx9QySR5/PSbNNpjbK/P/PoK47MxUl8gpaYJbQ8t7hDzL167ztYJt2tlnrT69Eci7b1tzIM2khBnfrHEqDPiYG+C2W9QLRoYCZ3xoEUzdHBNB0d/sSwzv7ZGs/GEc2vE00QMJZXi4w8ekqiUSSXrPBolkISAb37QJ17IsH94wiyUGYsxLl+7y7e+dmHHMzJojoVgO8RqMkJkkE0ovPP9+8iZPN3OCaHtMu2OaQxHaIrDxnyFgIi1jUus3FgF/kdub94lvnKH/MYau8cHeL5DvnaJ2dinUEhTrtzgeOecrK6TiCmoEcjzBt/aP+X41EVVL+rxq9cXWVos4yk+X/rMJRrdLjVcruoRqBKr5SyfKc+4f9igVJfxnAkffHyIKZp4i3PEfP/FN9pYxEwJTDwY9NvUlBQzc8jU8pnL1hhYcfJEPG7BODhlfqVILpNmrlClUk6T1i42+Xa2t3miF7l2c4lwcsgwHiD0ZMRsyLunJ+yPXFJlg9pqgWA3jTSX5eS8izwacd59gDW+KOnKehKsPSpqjOzKHdLxEs3HW8yWV3D2Hd752neYr6UZOnFy5y0iyeJGbQPVP2VgjqmXXgSLrJc5P54ihS59o0Z3bpnfbPYpKiYpFyI9JAjTaLs9EvPrtEIJ1RCJ3Iji9bvP7SSmIX4U0bJMBvaQXuecs4MO8YxCwivyf3y4RXo2xswMyFavEBgXPZi2ZjNs9ompF/2GW29dZjpuEaRNpvtndN65TyJXIwgh1jcRwhpXsyWebW8jZDRctcWcIRMCoTBgan1yqH8qhKCU0qnnYtDWMTSZlGxAFPLtP/wW+WyF7ugAWYsjDQfEa2kUSUTTEiysXcPxxxS0i7r15OAZs6xHMIuRcHXmE8u4gcfInLH/YJeb1zZ5+OQpV+aXaU0s8nqOeQMix+TK5euoWsh/83/5dP0ttoYdDlswisHocZOpHzDd20bPqzRGNrGZRCkzz2D/DC2TpyLrRHELW3wxqjFnMQYuOIKGZChM7AgbUJeWOTw5R61VMKcOTrLM+qUY5WwaxZ2S0jQS2TRZ42JZqrp0AzsWstc/Zvv8IXFdY0aciSrTtVxMr8VQ9ei0ugxjLu3TLsHAQ95tQjpHtlQHQJj1GbSmLOfvMptMuVao89b6GkXd584bryFJUyatiORyjr3GAFeNMchIjMwxTitAz71oFnqM8WIKg6aLZxQYC3EscYw5cnjanHDjzgb3H+9y+fJlxH6b1MIC0nEDtSjx8MHHpNMX3+nS6gpLNxaQ4jEOto8pz+WY6h7P7j9ED7O0zTExocTuUZNxINP4uIGoCMRdHymbYDq8mNIM28/wSmv8mXvXaB+OODweUykLBKMYcc+hVFcxEkna4x5h5DG3scF8QcQzJxz0uoSB8Zxbon6NXO2QSUxDk2MEgUQyM8+jx09QRi0WriYwI4WkZFAp1kkWipiBTzwUMApzz+0Iog32jHwuwemJTUrJ0RcDErLMaNwjFVfYKC3hij7D0YCUGMdIJPB6J1xerjI2L7Ld8GyX9HwN8WRIpGVJXC2R9AI0Rebg6RhfFfndP/gu6UqRwD5lrqazvHAJW4H+qEG6/ILbH4VPhRDo+WVUJ6CnePTNAZv1GqWV28zsLI7To6jUCCSRnjUmrS8RiCIT2yUQpxSTKpJ28Ur1j/aJWTPUzDrX8hrHZpdQiEhFAb6U5uO3n+AIJs2YiyVl6Z302CgmkVSXB/d3MCed5z61OjZr934S9eQZh+99xFBKEEgWubnLmJMxYlzCwuSjvkXeKCJLc+RrC7jWDG+Wem7n8OiceCFHXgFDifi4e4Sgprl1dZHX7qxiuRbT0RDTVSkk0yRkiVwijiQryPEMC9UKAI7Spz9p0mxZ9BpHmJ6LnjMQEosc9rvM6TFOz3YRVYNht8mgFWBk0wj2ATk9YuxcvCy12jJKRuOo0aKeXWXh2ibpMEBuNTESMroQxzUEiqk4tdw6ptPFt48Yu0soUozjxovFlHo8T2x+EcHr0+mPedY+ZNruIUoShpri6NkR5dIcjx+fsLJawx5CPVcjJccwKjEE3wRgLEzY3vkBB90mg6MDpMik33d4vPuMVOjjThwSJ0dU63Noug6KwqDn8/j32yipPKZ68RBkwgzjfRcFmaJRJOy0eXLQIWTGZU0jPhNRYwO6rUfo+QrZUYdm/4B6PMsrmRJK7wW3rY/2Kc3fYVF3scwpteUy8XSBn/03/jSdXp9Be0R3OEOJVxDDGKLjki0XcEyXpzsvNlQTwRGSHMebztic07CtCYuEzKQh7VGIBviKTLGax++52JFFPZun357SapioysVIO5Zdh94YQ1risX0AqDx48gAxEFHidbJJSKyWCLwpaqqIKljMoiwJ3+Gz9z6LI00/MQaFT8O/PBME4Y/fiZd4if+PI4qiT/cfJvnzP13m5pUbjHpjjOVlrG6bgRkghRNm04hsTgF1zLjdQtIMJj7oQYITJ6SUCnH6Nn/3a2f84q+ccv/xh0iyR0xVSUgm9qyPbU2JxRLIko+cVJn0TCr5NKetIYoqEctmiUcpljZv8Td+/uJ32//Ov/sLWI6FHo+RTYR4kz6puEikJBlbU4IohhjGiWNiTn2EXB479FGjOP2uzT/9F38LgK/9+q8RJJKcn7Wxmg20pTq6mmJr/4xyrcqk7zPonFFfyBETQ3RZAHuKIieZxuM83Nrl7//KL/OFP/9zCI6F4noknBleGDFfW8cLNJBlgkgkLbskZIfxoEvfdrB6Q2YBFFbrfPjDJzz58F3+4l//VQJ3RohNJlNF08H2fPTEHEx6+JJI+3yHdCaFKAsIUog99UkkC8RyJRQ9yS/8mS8A8Jf+8i8xnvSIRAlB8ggiHy0mIHguSSOBM7Mo5UrYiJi+SjRxkZIqs/EUrVxFion87f/0L/M//2d/jeNWk2q1iiU4uK0zVClGqlZH9Cw6nkM8X2FwPGQ4tVkwUpCFrOzjdjxW15f5sb/0F/hzX9rACqAQCRwdnrF56yYIWYLZjDff+AzDbpNhe0RxvspYHDOXL/Ho6R6VTJxGt8XRcMw/+O13ALjzM/8FkqQgSj7e9JhaIY+h+Oi6jDeDkT0knk6TjCcQKTDsnJKtVnE8ie4szm/9nYsfMP3ub/5jgkhgZ3+PmGTgCzKGFuDJcWTVQw0VtrZPQZDIVDJEqoofymhywPxcnqW5PK/ffIvv/tbfprtzzNDyIWMQzAQix6YxHKKIEpdXi4xcCW8yRtA0FtIwHPlkVbBjNnev1z8xBj8VQnBrYR41gDCZJHRGxHwDQxyRq68idhrotTxdR0UyNLodCWtgsnH9Et55D6wzQv9ipHV4+jZecMJo2mMuk0UKTNTIRQmG3Lh2m+kUlHTIgdcnm/axZkP8MEQNRwhhmmHrxfw/FXdJKiO82QwDA1eKUDwTNQWBY+LYJuNZSOTMKC7M4/gjCoUiw84IQ3vRfT4+7OIwYdDv0useUew02H3SQS+vc/xom0rhOldX77DbPmQ5V8XQp6QzCoPAJhxZaD9adtTjKQLPR/N9ilmDaiZHOpmmXFtBUeKEWh5VlUmHM77xzvfY//gxPQs8d4zX6pFIXdT2ujwhiOu0OqcoAxd3EqFnRaaTKXMpDTlyMNUJog4HD7fIGFlW6jWkuMPA79LtvNiaNF0TR1AYWX1KmQz5VIHAGiInQlQnRJd9dDxG/S65hWUOLBM1sNGLSWRDxnEuFsFmnknVkNFzKURBZKZncNwh6XqOSCzito9QCiJ2oCLvNxGSKtmEQjJe4qD/GNv70bguPc/tS2skIqhf9ymXFmieHSOmkpwGEr2JQ66whCOopJN51HyRhdtVCKbc2HiD2qT5XAiWMzaB7NEfDIiJM1T/jHgwJiYl6DaHxIM+Kb/KdNwnu3kLTYeZMMEFutMXC2WDQYexKzGLdLwESIqB7wvIMZiaLq4qIGbTGOkq7eEpCSkG0wGpkoYceTTPL37JenLWxpYTJJZquKLOaDJCTo2Yq5YJxw6xYhZ5FrHy6g1OH29jSyFqCppTC90dc3Leo/IJMfipEIJEvk6mXELvKBRTeYqXq0SazLtbT0mndSrpEsvZOU77Q6q1kGxMJAgccmGPqaDiT33gm4jjZ6zkMrgzgcpyFlmsMB6cUs5lGNEmXS+gKQnkoY4diygVNEZjm0IqYGYPMP9vlzwR9lBFB7mkIksysuAhqnEGokBQKjOfNuiMJiRFn5goY48FBqMmipGimHixquyYLmeTIXIYEE8mmJguetjibvUGcwuv4gg5bM8lmvl4touYT9J1+zT7DuhJ5MTFESW0kK2dFitpHU3NYCR05nMJNheWqc2VcT2Jk6lN5E7I1KrIe09Iazq//52PWcMmn764BpE6JhDH5GQBJrvYYYnW4YhsLseeMGM5HiJ5Iv3HB+TydcrZLL5nktREXL9Dr/ViW8bwZ4wmTbJGGi2hYM3GTEYj3ry3yMl5C8eK47jnKLUqQQxSmSQx2UNUBKZ0se2LWnrqKZTnKkxFie4M5kpr2O09Dk93uXrzNvHMZfa3H6EyI5eNISsgzXwW1+dRbBjMLqYGulxgfGwRGjkmpoVai1BK8/iBRipbRKtVODhuMTw8Q+xJTJ7uM7IHFLMlynkXLXhx/hnnHASJZEpkZIpoMZWMFnF8toWoahiJGErco5CqMZy1CI0K+CNEB3T1xYMiRzPQkjS7bdSWz8g5Jl7JoDgGZq/PXHqBuBcgaDMm7S6+7ZNfnGfY7+JM2zj2xS8ZPVcnEEMabQetLCEl88jFKupkTLqc/j/Ze7Nf27LrvO+3+r3XWrvv9+mbe87t7626ZDUkxSIlqoFsQY7SGEkQPxkB8hAEsRLDCAI4QeDEQQIbQQw/JIFsWI6cBBFgx5ZtWaQoUiSrYd26dft7T9/vvl979U0eTqWOHip8LsEaf8DEmnOu+c0xvzHGN1i820TdOUScXiDN+5w4MmnRZLG2wfFhBB2Vr/6MM/ilAAKxep3T+ZSFygISNZib+LaMHlXQa7c4GfcpKFV6LZflqk4yGoGpIM5FlpuLnH5G8rlOi821EufTGEVPmMoCtmAS1+oMzl+y3KwgKzolS+T47DUSfdKmSZDYeDjkClckX+LPyFZSnM5sjIzHhd8iK9X45GzAxp1v4HghfSvCiCdU0iKiKhA6EREaZe1qWcuNJoE+4+jlMx6++JTtWoU3r6+ScV4iXjjce/DLdOYRammD4vIyw9kr+qMYpZnFiJdon10eltAJSKIAz/FxVZ/d/iF31jdYqCqk/RlnJx2qlUU60zZlJcuttTcYTlr83M/fJ5crE9iXhGqYlbGmFiVRZDzoEtozEkvl4KzLaqnBQI5JNRdZWW9QayyyWqvT9Tp4qRxNvYEUP75aIyUgn0sxF3Smro+um5g1jSfDKWgK1xplLoZ9Ot0hkTAmnfigp8hFAlmpSj536aU0agUGnRPMxhrrdQEl63H8tMXKnbuMBBVBlZEqeQIUvvbzWzz8eA81kTg6GNIfO5QXL1l6zfLRNAhTKYJE5NNXHXxvwspyie+//2Nuv9vgo8ff5817XyNUi0SeRrEXk1Z9UqJFKV36fG75kowiSMSqhIyAmMkxm7tM4hzZXAkvDjgdiqhKiKOpNMSITEGmawUk/tX+OxmDerNG2w8IcLhZq/DsyT6qEbFUEkj5PkpK4OnzJxhmjkY5zeu9xzRri6TsEVnl0mtqdaak6pvU1rPo+pza8gYH+4ekswsMu0MWJh4H7R6bOZ3S+tvMRjZ2f8jOzpTubIDqX4XGv8i+FECQqxXJuRVsrcTEk6n4Bt60y1t37lOVMmSlu3zv+Y+4USyAr+G4QzrhhPxiA0+LKTYuGfFiRsYsCKRDlcPumPp2hnL1GqEoU61soad0zrsOiRqyUCsSyNKl+x25LJWK5MpXP0KqnMM2NS7GQ8TZCLHZ5IWjYusFnp+cMp86uHbAO7eajIIZmjOlmNHQlJhS9irX/PTkAkcqEgklfuPXv8PRi3Oa2QT/tMuNb9xle2ONJddHOHfBb/PBJ88wFhuMj6fMKn2e713eUo7dJptNEXhg1A1qwjKHr3aRzlts3b3L+etTJkOX0/0DJolKNPLxZnPWF68xd/pUS5fZl+PZHN9VeHx6wlIlw+ljG3kKk7lH96CF2ijyi1/f5p07G1xM5mTcmI8eXRBeSzGxWxjmVRhqOmnT3N7i1es2QraIFdqYxJzujVhbXWCvNyRMNFJpH0XTmU0sinKatBTQKKY4OTsF4I3F6+wGM1y7S9ZN01iu0b6xRtRYBGWOUYgR8kuoZoOJE7N6bY1ea07GHRNPpjTffBsAERlNzxEGKRxnhqc5GPUiQTND2xeZzfbZ/nNvkoQj7LlPqwNb5PEvplzYe8Srb17t22DAQjVF1qxTylTZebnPSn2dQrlIsVrk0ckRiiZzY73CoBfjOQ5p/xShPUV1rsLHVm/EWNCJQ4dA1zicieiba8jjFtFwQBBZtC2JYDgg2MwymgzIVov0Z3NyzTST3cv9X1i5w8A+Z/Kyz8SZE96WkWODQimLLkzIV1Te3Kwy7LjoORlvv4umlRhII+ZRjbl7lT7/RfalAAIplSalq8wuJnhCjfORhTOy0HIuugovT47JxDJTBURdJVNt0jkPkCsGzWoWf3AZdMinIjJaSH/YR8im6J5fIOpjUmqKrBTjhXlm0QyfkLk9IZdJCIQYRRQopSQK5lUevZbO4CUOkqnTn/QJxzYjB0ZxgaAjkC3UiEMbSyhwPu1T8mRUQyUjJgTWVYFHHAdM/QEoMeWlOhfHz3l4fIz36pTGW79CYXmKZcOJE3ItE5ITx/hOGjOdYRA4NOqXt2bgRczGY1JmDsf1CHUBDZWTkwGBdMyrnSOiA4eUKjObD/C6z7h+9zpnMUwnF6RLl+OokkoSxYgy5BubeJMxd6u3+fTxEQff/5BKykQezSkZBvMoQEhSuIMx++E5pCKaK1cglzUUHMfH1HVkLaY1njPxfDJpkWa9gO0KTEdDRHdOYE/xXZdYUymmK2QFkcS9vO3sKEE3JIrNJuJcBUXl5vYWs9waimqTMMTrONj2kGahgeMLKPj0Ly5Ya9QpfZYQen1lEy+MiYoGnuWhGBIdTefk7AyhlqW0qXLQGVOJDJZqGcKDU0QxgkhFzmXxpStSvVrO0OlekA5lIiKiIGKhlrnkSLw5S5Uq4XRCOooww5CGoVBJmbQmNufJ1X808B1kPyKzuMqk3SNXrKISEFhDFosi05GDM4/JqCoiGrbgYLkWmVIVQZGQk8sjet6Z0J6c8M2vPuDVJ4ds6WkkQ2dgu6QVCTI+Vmjx+uyQG9WvE+eraIJO9/UrGitLSPbwZ57BLwUQLC5dY5iIEI04sDOMH77kFzbfYeflM/qZAk7HJ9YkissrPHz6ED9yKH/rLSrrJmllRjl/eZM3s5BNZykvbWMFEhfejFanz9aDd3h0ccwTv4+pxJyePqVipCmm0mRDFROJyB6iS1d0iuSP6EiQyS/iGYsc9jsIuVXmkc7622/ybPcxSknij446FKV1gkzEiioSzAfE9pXAyURLOB2cImkif/t3P8UMZyylpmy/8RZz02aStIjzeUxFQS/mKawapFduYlkDZm0P0bskHiVB4Pat6ywXslzsWly4IUJGJ3YkXn7cQkiV6Q8csrqO7btM+hPM8TmhlGdraYtU4ZI1Pt17jmFWefDum6wu1lhcDFl0iriWRP/wlGF6hdNpjh8d9mmfHRDNPU6OztkNDzGXm8RcPZ9CpcCRLZNLJZQVlSDlUFheIVQEDo9PSZtptq/V6Z8KzEY+fjAmUUwCSWEyHGMql6BSqG1ycviIZD5j5dYiG4vb7AwsjseHLNy6xcyesba6hJRAo1hCzMCLP9hBQyGZDnA/I4u17Abj0wvm/mtSZoIGvN97zcL9ZdRyQj/p8847S0zaAS8+OKa2eY3cMGAiptlYv03ndHz1U8YaVS1FanKKnPhUz8+Js1kq8xHOkc3GQh7HHbLu57DjhJMXzzAKIqEl4PyJ7EtX8JhaQ/K5MrlCA/vkFRubN2gsbREeTFFHJ9QXKjiFEh8czyhtbbBWyzG1Z+jSmHZwyTcYlSblsM+8d87SdZhMDilpDULX4SicoL7uMJcc3nh7kdjssn7ToPNswptvrzP205w8uqp/+CL7UgDBq1aXxMwzNLKM2i3mC3XOxhFOe4TYDRhezGmsb/LwxT4TREQlwYotfvp8h6+/dwsjvlwsqzciVe9jOwIv22NSjRJCWuHZyYAg1DiYBSxrE0w5hz93eNI54+2lAlLKoYrI7OD1598UBC5Z4xbp4hbSPMI271Kur7IcZTi3Je7fz5L4PmU5opL2yScu24bA8OkPmA+vqtgWtIRZrYCXFsiHq0SiRzXfQHRniHmVl9YuflTBKBhMs1Xyb2zw4Q8/RfM91rUaheplbfvtlQqtYcxw4PPgzVu8OndYvnkHK9Mh70e83Dnl8GyX7dUqpushlAw2VtfhfEjWlinVLlOMi0qKUtnE1UTW3t5GHMicP5tgaWlW77zN+WDCNJfjZDLh9d4Rxy/2efb8xziawYNSBnu39fncEikmHg+JdYOpH5PNVkgmNl4w41Z9m4HdxW73mQ36REke3SwiaxGzSMbqTZhbl8TjeSwwcyXovuR3P/hD/kL4HzBQ51SX77P39AWiOEWJHfzJnAs75FfeeoujJ4+4t7LKU1fh1trNy7npE2aiitq8z9OzY26syzyoTmgbAWMcfEHltNVlQhOtkCMtiByd9fnK7W9zcXxO78XV3GJDJz/y+YpZI+xELHge2qsXJCMLIUy4JixQFmccfXzGZmKwpcfMgxCzWGPn+c7n49RyVVYKDcZBGtmbUsrnSI+HzIZHmLZH1BuQyi+zc9Yhyi1hpSucv95hKgakgxnlzGUh1JPdU+6tFyhkRX746Hvce/MmL18eouQynHkhol6gNx0xeHTGMJny7/5b/xEf7XyXZu06x90WpbWrtOcvsi8FEGy/fZ8PHz/iaOxyfPyMb9S/Rf94j+9sr5LyPJ65Q+bTp2wuLfNHxy9p3i6TFixiQWcyCylnL3PWdz59RP3mA8rFBbYbKSzFp5ArYEcGE0lkurOPbTTxhw7fun+T+cUxhmThnpyR6BqlZuPzb3r/Bz9l85e/hjtNUM0yFWmRVy8HVNfKCKKKmdLxhDnW+BhVlBj3hnRsi2joUjevyhivVfJIkz5jUeQkmpEhwdMzbL21yQcHx7z35hZ7rWNEq0ljaOGLNt95+wb91oiLFxHl2gYAcX9KNRYoVjIM2x2WNZMXLx7x9bff5cWjn3JzK0+sFTnYPWStpHDzRp1Pf/KPqV17j9NWm/+Pv2pWdGQt5KR9xFH3NjfLS0ThMZPhCzaaNRR5TFK0UY2YdNEjt2DCWQpJ1BnNPb7x4GqNZFvkO195QOB5RIyQBIG5EpFyEsbTc9zJiFw5RV7ySaVd6kaeKEjwvRRiPsN0dOmuTsQiL2Yq2YuAcl7kd773+9y8s81v/YO/BYsbPH/8RzxYqXFtOUstljn80U+RJZOf7Oyy8OCXOJ1f1gjYUYZ00+Rs3KWuVTltnROtK3z9177JD3dekDN1BpMRJcrIQZ50S0RRsoRjDf8ij1aoXs0tSHjz2jtE+3uspS3Kuk9aVPhqfUZFixl3HM4vTqlHAsvNFQIy/PHrc0bahIyhXo0TyfRPj7iYj8mVCuSLC7SGPSanAouLd5G3s7ya+vSiDFpKIJwcYi4vowxt5kmdxVurwN+kef0bLG/4xOeP+NV336MXHrP29jqV5TX2/uVP+PFHn6D5AqV8jm80voI+8flL/85fYe4eUNyZ0Imu9u2L7EsBBN3+GdXlMm5qhtdfxa/5bNUXcHohpwc9Nu4vc97p4ab7VFdi5KjPamadHdnDCCKO2ycASFjcWFylml3iccfGrJUQVZVk0aTT7/Hn3/v3iAZz5vsfU9FzCF7CvZxEub7N5PQp/bPjz79pdX2F/vkFO/MBNhKNzXdIfIvdD16xP/cwdRUhEpD9AQvZFNHwjAIZlgsZ5tZVx5xSrsT5uIV9tMuSHxHhsZHZRBxbPI09vEUAACAASURBVNi4xfs/fsWf//Vf5Xsf/pSBn1CtlbE1n4HfZzjv4exfvjcNVWdo27QPDqnUVsikEzozAWvcx8imGAUqrmuxvZhiMZfD6w25c/+r7EwtYqmDN7p8YnTbexSFVarlJdyRzVw6Yi4PUE2L/mRC9XaNVFagYrqcpwNEdQ4jl+WVVe4uLZP9EwIXo+MLrEKapeU7jAKF1PAIw3c5s+bMrSHri8sEY48NSePxfhu1nOW9B7f5Zz/cIZfLgnLJ7cxtn2A6Z5bWkMKEg/0dwiTBds756F9+QqWQ58WJhDOY88adGqV6Ay1QyZHhw6dDGv6l+vRckfnu93/MaDRl69o2yfomfuLy/j9/RGk9y8HjFnqxiiCnGPQ7rGm3EGoGjx9/DJ7Om7/4S/B/X85NcWJO512mbYFrCzW+upXFOuvhHFi0JiMGpTpnPZfvvHmDn+zs4KZXkBol5lbCxvIy/PgyH+H0+AjRS7FQLTPr27TcDvp0wIE1YTJb5bqeRQ3H6IMpqTBPGgFh0uF0aHHzjbdplrcA6I8txnt9KrrOUjrkD39yxGpKpj+aMSulaT+dUi4vE0cxWkrjeqPK+cETFkzQGyV6D3/2GfxSAEEQZZn1znBDHTlVIVFFfvv3fo+v1O+x1VignfeYSA3GikWSL+HICr3hkFBR6fT7pD/jeFYreV59tMu05JAQUSxVKWR0vvvdH3I0nqM9dojkMdHBAcN8EblzgaN65KcCedPDGl69EeV0nqE9Q5IFUprK6eF3SalpZFFgrZKhO2sTBWBKAmY2RcYo4gwi5Mjh2uY2cNli7HDnCa7b5mv3F/i9Dw9ZM9OUWgP2d+a8e7vG7VSNoz/8YyTbI9FzDFrn7B9OcadDymWBRx8+AaA77ZJOlWhU6nhzGE011pa3SKY+S2qWD97/CO+khR1Nqdy7gaFr9OYiiWOzXFYRo8+4hkgkHgy4ffddMpaDFQZ8erjDo8cfkrZFKrnrrOdybFzb5vq3v4WxdsLj3Q5h3+HV0wuapauioyRdxXDSFNMxphhw7/Ymu7uvyVgic90gFSkcn+8RL1TIxxHBWYePPJv5MMKxJxx9VrcwPm8jlxt05+e88e238bttpr7KuyuLyKtnvPnOLxAMZmzWVHLjEWlBQZy6JNUa3tOE+Wfl46Wb18m/Pmb13gqhFLGz+5y17TLOdIgsV6hOHRpCwnf/6Eds5NIcD1+RclWm7TMKxQUujq5Co/3RmLPXNmFvwJp6nSCx2NvZY3nzBt3TNvthglrK85EX8pISXgK+XGYUzbldqX0+Tm7tFml8yjWZ8dBCSCL2W/s0jQo10yKUfFy/TZK2USd9Cpk6RTVH6XoKMx/Rdy5D49VKE1udcNo+4bsPf8SzkyFn1pie3eOT0wmBkecbuSb22QAvfIF82OH+8jpTQUZOlTCbVwTmF9mXAgjcTp/WWZ8JGme7++RL16ncWCXUYdRwOZ+MEda26E/n2FOVMHDREwklzmD1ZnjGpY5eNl+gUTV5/WoXW1IJbZVKPc/Jx58gVW4wbj2nkAmIxz5FKWTmSkT6Mq8PPmSlAc3iyuffFDpdjGKexnKdVmtEtqCQZoZSreGFPltLDeIowZ76SEmMHgeUcwLiqI83v1rWoVAk9Gb8dGdK5fq3Uf0LzveHRCmNQFunKMY8+uAJN37tPkubt/mDH/0TYnFOb+6g+Qrzz/QkdCONqkmMPI9cY4t2zyejZgmyJqfDNmktT3p1m0HviKhcZjYbomc1EsfGUBW8z0gn0ZcwSyUWMg10NcNgekQ8m2CWCnSlPkJ6xjt3M9hpi5JaZCGoc//6CmFfp9PuoYhXc4ulNElK5v333+et228TTWds1JoUwzyimWXkenhxCa9v0pRVPDGLfdojDmWaC9co5Gv8q+8/pG+fIGdEbt/a4PnL19SXs6C6tLvnfO3aOkoYMhb2Wc+tIwchaqFGqMwobS5yIkpMnEuQyxWrbG7f4fhgj6N2CzGn8cn/+f+g6TnOpNeIjoG8pMOrPbq6ya16HjSf1OIyYSrD9XtXjUm0UKDx9a/w5Icf0srmiOcBg9XrdI0yyb0bjPyE89YTTLXJU+EM0zDQ5CUqNyNqaxufjyNoeTLKnFJKAEkgp/Up315j3JmjJvssSiHuUo1KJaJ73KVcL7GxVsbNNTjzF/l0funSe2aA6oYklkd7Z0y5PCGRDCanHXIHE2prec5++pBr9UWuqxIoAp8cv+D23ftsrW7ww5dX/McX2ZcCCBIjRyHvcfbyOWokkDWKeNWY/k4HXc8R+SFD/4QbSxsojSbW4TF2y8Maz8mURAr65ZusVi7x8slPyGYW6E0c3J3XnF24LOczDKanlFJ5rHGLa/kS4/4R3jjiycEFBcVk7kyZDa8aUzSKBUJhhuqdc+/OdbqTMy5aXSp6AWvQQUy7rC6ucHR4QiGRsIdTlHQaMxYo61cpxktLBQ6tU5xhxM/dS/HpP/kJa+s3sDyToigwSVy+/Rd/no5u8PD1Q4b9KReDUzYWaszHCZ54KUzhWzHu1GMWeUw0GyGAcrGAEsDxxRhZVbHDOc37dxB1EavdQY6LlPM5CosG7mcS62/c2CalZWk/PWTvcIyf0ykaCzxNXtHcWmJla4v2qMX2SpOUnEGpqDRKFXpehOFK5DNX4cPRrM/DV+fUyiWs1hmvAwvTFJn5aUbtQxqFNFIS8+mjT9EyeaLAwZJiPDVL0pqRrV1yO+2exfpqjsSek0vViBJo7R7S3F6itrROe2wh70i8OjtkNauixSGn/SGHw4hArRClL4nQlYVNDvK7THIV3qrkmO78mNTKAmML9rsxg9YhrY7CbGQT6TGJYZHN1iis1yhVGyilK2FWI2ew13rB2jv3uVBEXgUz0ksN+laCoSrMrCmzbJ2jlkTz1gMmmkuxoDHLSnxw8OLzcTqBQyUTk459CskBsS9jnb0gI2VgJqIHCVNrwGQYcPerN5h4CenEod3uc+jmGBuXAq87vT6L63k6Z2k2tjcoZFK82vtjtjJZMqsF3EyO3vM+OSTu3a1jVK6TclwcNcuzfp+OeqUs9UX2pQCCtXSJYDblrfqb7Mm7DC8OIRHIr5SJ4hg9bZFSa7Tau6ykGyhqSOiPEGWJ2BeJ1UvXMBFt0kZCqqwhdwegzwkmEs92Box8h43VFSIx4FX3HPyIZATFgkohq5A2BQT5yn0qZgwuJlOCaUwvsEnlMqyUygwPX1Eq1sHx6O09IR9ZZIWYhUqe7vkhehxQyV6FId//6GMEz8Vzpnz/X/wEyTU5fv6KVKmBLMzIGib5ap2TnT1cx2VtdYvV1VWqy3Uev+gTji9TTAv5BrPIoCrH2HGMYWgcHL5EFMr0BJ2WZVMQA4K+wCwMGWkGaqBRTCKsbsB4fBk+iqYeY++MJI4pZnR2zg4oXFsAWaVqqPgXcyr5Jq0Pj2mHLWYTCy8JUcsK5simfXbVvOParXd59uKHXOy3GLdFyqKNruX55tfuciFZfHTaJponBNk6h60LyqkMZqGIuFgk21ijtHgJcru9LmqphNCfcWOjSSw4vPEr30J2HBRDoZ7OIWzZVFI5SpUytuWQkT28co5kpjKeXmbN/eD5p/Rx0VaLtF6fUzBWOHl4QmSC79vMei/JLd/kK/dusffiiNPzGd/62jcp3V1jboWE4lXSzVCGM2HGIO4ST3SMXIpbt+4yeHnIU8vDUSVurqxR3kixuLhBXrPIawEX4z6hc6V0lZBlOBiyWfQx1VWc8ZSCIlJqLjCfjlBil9VFnfPzI4ZTsBx4Mo7xGlmObAFHvtQj+O7Hf8iyuU25tkE+1wDnhPq1n8MwNO4u1+kfHvPeW9/Gn0c4tsRo16LQdLlV/Sr7Xp1w9uRnnsEvBRD0e+cctA9ZL6xQSi8gZ3XOj7ooskRr2AHHI5M6IlEjDicd8kaedL2Ge9bBCAPM+NJ/Xl56j588fow4dFkoZ3Hx6PkReV0ln8+yubCAIoUkY4s4DMht58CP8QOHcimD4l41ppClNFHngtqNInKhwKg9Qa0uI4geeTQSe0boeuS1mHwmhTWdUlY0RiOXw+4VWegqWTLFBRRrwu4HP6WQKlDeKtHxJzw5e83StW8wCFWmgUQtt4oynJFbXaO5tMKL/ffZvlPg94FGs8j8cMTFRZ9MYZ1SvY4TCXT7h6TTKhO3Q7GQQ8/KlHJ5hDhm0JogGQEkKQzpEuSUqcbMk4hiCJyYjFZFCQS261sU0mnKpSXaz/uQLeJ5HrIEXpJF0WSq+UVyV3KMiIU6gZ/iotWmTYRGhKGN+Qc/+B7Xb98ilzXRZRUxlbD9xpsk0YxisYyfLbP+xrsIxuVNLskyriOhZutYUoHWvMvE9dle30Qehbwen7CysEqYzrHnjZm7MUZ6EU+pcOE4DOaXHtg//smPuLO0yOZKAzG22PtXz3jiiHxtvcLmgyWe5xXkcgM7mqIvN7j95h0m/pTrpkG+YdIeXyXdjII+qiHTdY4IPJN8dZkf7z1i7foCpVSB7tRC1LNsGzJpYsR0DnfeRY91Rs6VPuCzsyGOGrGRMRHnI9qOT9ZL+OmjTxnYLg+2tpA6I8zyDXp+jkT2MTIZOo5Kz4qZOJe8VdrIMfdN3n73Psp0j6cvIdQMFEPm3pvf5vv273E2UHn7F2/T6lgIY598psFuJ+Ljsz3aJ7vAt/5/z+CXAghKqsg76xvUG9vsd9oMww6rNRMFiRv5BZ7uvebNayUmgwn1Zol8McNkGHNWkLixUiKT/ixrLtCZ9CUce4KjmaRLRQqVFLU6BIFEQZORJB3XDLDcmOsbSxzvHmJ3zui6OgRXiSCxK5PXCvi2RDTvIfkJg4tP0GWNVJzgTCaU0jLd7hBHU8kYJs7EIhOaFJUrQq1WXuLl3hnHB09JGxqZegZfirl3/+vMBZnjjsWzwQGS1WNeLKIIGnNHYdwCo7rMyfNPARDjNGo0ZWvjOpKUJ/AjPNvCmbWZjSLuLF3HOjlAUF2coYwXxlSKVSLXxrc94s8EXp04RkpJhI6PIKlooUviKIQuuGqEIuXRRJ9USmPm2QiBiCqIyDGIWoSZurrttm+9y8HxAamFFYatFt3egL7oMjGrtI7OWV5ZJlvKsbJ6jcZaEy/ySGkZ0maRQK+iiZdPulmUJsxXkOIR/TAkEAUCSWd/EDE5P8OOApT0jKN+D1NXCT0Z3xIxsypn3pTOZ1JlF3vnLC1u8/D5Y9aadb75l/5NWv/odyjcbzBXTUJ7m5WVJWx/SmnVIdEVyjeX6YoJJ0fH/C//2z/9fG6RqOLJLoZeJU6JjP0phigyVSwkAXxxRm2hTOgE+MMdHn/wnKyURhZj3PDq+VTZuEdIwEejE8ThMYYQcWr32D0eomdznIZzZpGI3LHJlitEcp54qCAWC5Qq6wxGl97OYq2MuLnKweCY+dEzEkVkqAgcDyz2P/g+neGYVK3Cw/4JYSAxDm12pxL1lM6FN2OgXz17vsi+FECQUh0SXUKyhlR0nThQkXUVP5xj9TuUdAkp8shkZRx3RCb0SKclsvaElCyhfFbt1x9Z6JqClkqoVAx2Tg6QVQ0jrVMr1FgtqkznAXpOIw7GnB3uIosyoiaTSCJT68o1tH0fLWuQoEEIShygJCK6BOFsThSJRImKmGhIioGYyOjZEvHE5+j0qoptffM2Tw7HpPJ18kpEyVwg9ufESomqksFLTGaOh2KkqeeLBEqR0TSgPW9hxzPq2cuCGi8SEIQEEQE5mCOFIGopprrB3JrRGczQBJPAUwkJUVWJYXeEqfiEmkTKuKwRUA2fOFZJwikTz8Ed+yA7yGKIiIgmzvDiGVPbZj6eMXYdDA9qWRPRnDOcX/EfpyOHXHOdijgk8ubEooigioTKBNv2mHgReuRzNvURehNyeh4xl6OiFhBSOQTxct8EHQazOUZOJpJ8iHTitIAgKMilAoE1QBBMkkQi8QWMQoVAnKJLaRIvpKBdgpws6lijkMRVODmfom4YbN+5y9qNRYZzm2y+wdbqKsfnJyROn7Gnc3pukUliTgYesnaVRxC4ErVGESeUseKAYesYcga9iwmFXIbxsM+0kMcZC9jTLoIoohoylbRMq3dV4PNo/4x6SWU8PUVsdammZcKJzbntkRcj9lpzfN9DMjVUZ4ysJZiLVaaTCCEfczq49AgurAkvTg6xtDmzixblxRozLeLoYsT95VXUioNrCsysIaonIuo5+uM+wjiNb3uI5tUl90X2ZwpFf2Z/Zv+a2M9SKPrZGsd/Zn9mf2b/WtiX4mnwd3/7BbuPfsDMdVFyBs6whxeOKBg6mazKdDCksHkTx43wgoSMkWEepXCigGQw49bNLX7zL7/HX/sr/zkLtRL2YEa9YRCkTSbTIdlCBYKY0sIqw/ExvmWhKArufAaeD5KIJIA9GPOf/Xd/B4C/8Y9+nihSmE8MIiHDciXLzHKxZjZypkhk6viDU4b2nGK1SsawwfdIwh4l2ec//ovvA/Ab7/wXpOMuueIS9aUlRCFiloQUC3UKKYHDV0dkltbwPBHNGzENZph5mfbrDnvnIzzyfP/JX+e3/vv/mrmv4gYuviwjyil6Z8eUmjnEuUuuKCApKSJMlHyB8WmbfrdLQdcYjAZUigZ/9W/+Xf6b//aPmc8tBCFkNLng8OiIcs7n7OlLMjWD5eYCsm6SzpaYz6dM/Qh77BKIEdXlFczqEn/7N/8NAP7H//LvIeExCyfIsYQoRURigpGSmUznoPgM+i6mqiKoOoqi4YUuciwQzAMkVedv/J2/xv/6t34Hz51z2rdw/QhfjcmpCpOJw83lIpPYoTNTCL05+VQRrRjSacfIYkA2CXnr527y67/+q/yHv/nbzDsHzKwRWkrDsRwEXaZazuO5fUI/jSe5yGmTWJSQjQIpVAgcRDnGGdj8H3/vvwLgd//h/85o1MUWVJYaJYIgZOCcoCklEh9a9jFquEgzkyKJRFKZIqlSjv7xPkM75jf/k78MwH/6W/8zA9th3hojBCbjix4L9VuMJdDUmJMn+1hKio21GtPWMd7c48Eba3jkSESPa/cq/NVf+w3+/v/w15l7NonfpalnGY/GqLqKIol4rkCuVGV3Z5cQgZXlMt3RENmo4s/7yK5Ab/6zne4vBRBY0yck4gWSKmBmRVw9jXPWJZtOM8ChdK1Or3/GdOayvroCmsz0pIOihVizc+zx5dteSafxfQlRV5EikWamSmAW2T06wUSk3XpGqCs06ougSIR0cIU5MEQwCvhh4fNvUpUKnZZDJb9EkiQIvTzTfpuvvPEt9gfHvDhwqJaW+PpXaySKhKbqvHz9KWrSRFfGwCUQlG7cwByFKE4XXSlQq2q0Bgqm6JIYJpmNZVKxgxjE3Lu3xKuTFsedc4SiRnihkMleVlZO22fIxQYn3Tnz2KJUaeKIImouS3c6YtoXkUUXxZwQTC84PrCQBYHQ95AUmYvhZRZfJjkkmg2IIxFNmnPvXoGL4z2ubWW4tbGGOxnjuDN8ySanKGQ1HSkt4ccCvnBI8ic4giQcEGkRieOi1RZwoojA9xk6QxxNQIt91JLK4fGQpWspXN+hlEtj6hn8KMCdXL5bPX/K/vkxrqfhVEokkkLsWKwv5jh0I1JyhjhSEFSN4WgKUkT3uMP6yibd4YCLi8tu2Ibpo/gCGTlGSINdLTL0bKSiQjyGctXE8X2Gjo3ve2TjgFScXErgjaZY3lVIpFzMk1+IOehbkFLwVDid5Pjps0cYSgYNl4J2xNG5xM+9e5fWuEslgo3tTbb0Kw/8/Q9fM/MsmuV1QmfOpN1BtUJmnojr9SnW6/ReHyAVQqqKiq0EHOy1EdMO3thmvXkZWQndEfgTkqDLwJ+hF+pEvoDli5zOJkjtA9ZW60SRTCD45BdrTKwuZlakVEiTdP8UCJNE3RNurtVoTfsYVR135CFVV5AMGUXLImUbrNVMeq8/RdAE+hevMJIJy9VrnHgQBpc/Z5gScFWBnCwgpBQmgwkiCRkiDs48/J5Lvlnk0O3SXMyxVNaRQ41Xu13miYUdXIV9xjFU1pootok1GnNtrYlqqPhoBPOYvOqRktJctBwSSaaUt8nmKnz8yUNqX93+fJzMbMyKaSKZAoWyzu7+KbWMRLGyTEcV2N97SVYxWMxFHJ8fMOjOkEXoTgRq9QZa8bJrkmGmEfMZUjObQcfFDyeMbNg7v8By5yxkKoymY3Qlw6jTZRYmGKkckaGgmDIr0iVDb1/sEQsh57MezWaZdCpNmBVQzAyf7D/iWr7JzPHwPAiFkCQJyVY0RFHCSBSms6vKujBykKMYXw04bh9jmDoz38fNZDlrTTC0DGYxR/5ejeNem4VMCUeIEUONdK6IHVyqLz1++ZDG5ltMQxdDjNjtzmgd9Ti51qBYr7EQFDGKXayhS9dqoYcycjZLEPRIF1TOXl7WmrS6p2jRlOVGgZQYsTdxKJsZEk2lL2TZP+qRzxYRBJt6IYPh2aR9CQMJLWNw4V3JsC1XMuy2Wsx6NpI5Rs5EhLHDysY2nalEdmkBKWdyvWJyMTxief02B6dnjC9GmHXt83FyLZv6+jKvHrd5736R+e1lsp5Do5aj3wowij7rfsBXajLvv2xBUqYdj7lVX0UupXDdy4zQyOpT0UVETeB4NGY+FyjWi4zOXQbODLWwxKmrgepSmM9J6WkcR8RYLDMYTnGUPwVAkCobpM0MDc2GtMCNxU1evrSJwzmxN6Uz9Nmzj7m9fhth+JSCKrN0YwXTT/N84LF187JUt1ErksgxdmtOtZIh9j3iScLhqza9kxFn7Tnb+l2Wc2VSiQmGwqBzzFyaY/sOinpFmbzq9RBFj19+8E3E/SMmbsSLs302Cjp6ReaWatBYv8bD8yN8vcC43yeXVVh74yY/en6Vs25IIbNeh5zsIgd5CukJw4mPEC/ycO8hB4LDVkNlmknTO31COptnbekem67EHz+cY1mf3S5KFiWlUsymsN08nixQrGdRilmsjoKeBT+QSFRYvHmDTK+HJOYpZ3RKXkCzernVZ1gY6RxRf459dIxTWyROZOZCmuxcRq8lDMZTViom5sY1rP4ZYTLAiXSO2kesNa5afpPYpBQVUU0hxRYfnbzEi3QcI0Qvlvjk1SmNWCabjFiIE8azMaHr4Mkhy+klTPMypKW6Ca4Qk008YktF1MuozQxCFjLHPfbFCW5nQrVRoVBdI5gcUFA1VLnIzHEox5f9EfQ0VNQ8umBhZnNsSHOetPvEyTLDmcLFRcLxaMj91QXiCOr1DAYe8STCnvmY5lXYd/fT77P54BpduUomI7M33qVXKHMcVVBLJt99/gHf+aVf4fePnvJGJmG0d0BemRMScXftSh1QiB16zw/Y0BrUkgYzZcgoPOONRgPWFvEnI9pxSM7ocqMsEus+naTA/v4zdKlCaeVSVTuYXpBeKPD6YMxULaDpNuMLCUk0CbQi9vxSBcq1HVKGg5okhO4x9nCCOBmhpq46fX+RfSmAQBENpt0Oetbg/KTD8OAUN72BnCjUr/0yRxcv2X38nNnAY62mMZlb3NDWaI/PWC6lySiXCCxEHrbtIekaW2sLaKkC457LDx+94klnyPHOBc2VBTZ/5RdYWF8F6ZAne5/ipMucD/bJaVfxX93QqBsa3c5TND/NJO8g1DSs6TGJ54CRw/YtIicgSRyUZpGj7i6i4ROLV4lJIiqzUYfe+Jgk7RJXR8wNFcc/5wgTpTrnWe+AgaWwntIoaSbGuMu041PojHnj3/73+b/+KVSbNaaVNQrZIhiniIUFjp6/xp9bFLJpikvr6KUphBZpPUcxm+HZ/i6ZyKOytkYwuRRLSSYTbN8FMyKxVRQxRhJcdMHBzCeUCgqfPN1lOjgk5XbIZU1m4Yy0IZBJw2L1KsRWbhQIpQA9ieheDFgoNZn4Ai1bRnQMKukSS7lrGG6PlH+OaIVoocOyOUAbC5/LZyVIxNMWlewm//zFCzbe2aSYKaKlIuqLHvJRhxdemk/OLqhkfNxApVbSsaIeS4Uc1uhy36xZiJGVCJwJrXEf0Z2yUb5Oz1eRwxphGLBZMSkpBo00hHGCmc3QnR4RzgbksldPw0w9j+XJbK1VefrxS6a+jmGU6D0+IGvW0a0adtvkF4v32X/xU8z5BKkw5C+8eY+0dXQ1jpRDtnzu3P4qgdzDNAXWVisYpTP67T1urWzwYH0DR1DotV/S271g7eYqWaPEp60+H/7BZUag640RM+sc2rtsvfk1JrbNOJNGoMxJouKe2jilJpvXdKxoD3d4jFxeYNA/p+ZPEGZ/Ctqie+4YJvs8enXO0tINTLPCbucVZ1aRt258gxubG2zfbjLrnnNno0wqcejuPqWZ9LnofsjLTy+nMZycU8hmsXyHT9sO7965j45HZf0BxsuESiZFSS/TqDRxhTl5wNAVRlML3wvwhSuPoGYWyQgghyJiWSBXLSIO85zvH3D3xiK9ccizRyeMLZvVBybjaUSmnsHyBzSubwIfA5BWfG7fSRPPV7mQhqQXGvyzH34fyQ+YZ1epGjarRZ/BySu0QpPDhz/i/AcHKNM0Z+413v6ly7e9pVY4HwRM5jaLWkw0PuKraxVCWUQ3Fc7OjzBlLsujQ5iXqrxVytFpddDKJeLwstON2z9DLuRJN2SOZmOU4ZRyNodvzTlyu6SjDBu3K/iGCuU8nh0jRCHd6RmSFLF3ePD5Gi2VFHozqIQh73zt5+lNQ1wtzUVXwJNryM07ZOOEbHGBJFpiUXOoqy5n7SFT3UFMfabtpwjE7oid4Ij6apbzF4/JL64x7oWYQ490eMi760s8E3bQjEXEWpN8r4WeCIycj5DtawBUKxkKcZuL/RZpOU2lXiUMUmw2V5DSCgWpwBvbJcrSBNEI0SYjJjuvWS7nUXMazpWMAHklxe//i5dkxCMSbwEz0rm2/RXWU5u8OB8iaQb6H03IVkwaw3UKBVid2zjHoKFpDwAAIABJREFUWdSto8/H+fhll63GGrgut67VefTyGd97/gnKnyvRYZ/jWRtDaaC00tz+5irqe6scHsKL1gRDz9H+jNup1HXa/THb7/wSR60iUXMTW60TJSW8icrKezc4PGvx6afPqUgF6obCSlkmLWqk5AN06epy+iL7UgDB870LahmJLaPE6eCIr969xqvIpVJc4tWrp3RKJVb1IVlpyvDigowz5eL977KUr7KRL2Gbl/JZSiSAJiCkTLIZ+ODgmIwvMx720YQZNcPBzOQYdNs82FhhGJ4zDacc7r1EDyOqmSu3NxRl2nOLILjgwRv3ebG3j0wKz5JxnkUc7J+BkuPa12/Q3h9QvdGgjYY/cWhs3Ph8HEVIY2Z1nHkfe9qnM5Cp3lrkFJf1Xy2zunyDR3//f+Lt+2+RcSzy5SKL/y97b/orWZ7eeX3OfuLEvm933/JmZWZlVmVV9VJVXW2728byMBiDZpDglTVsAiF2kEC8QEIgNBrwoBkJWcMIGZiBmRG4x+6x3W27u93l2rMys3K5eTPvGjdu7NuJcyLOibPxIoq6LU2rXyBelEU/f8BP9xf3PMvv+3yf77PnkdVqrESv4tjLd6tHiBdANVHAbza5ubOJ1x3R6004PWtxbX+HgTniojdj5Fyy/ktfp9vtczRx8bsmQmeZET68f8DW3Rsk9SzOPM7z9gm/9lqaqaTgoSCoKfIrEk+7bU7vfUzcyKPLYxaZPMEkpKxdBcuBM0MPXdbkDGJ/QiVWJJ6Mo5UKqEqK0WhK0gcvtCiUtzB9l5n1nHK9yGh6Tjq59Lz+QqIwD0lFJmeDCfvbeVJJn4XuMndGCH6I07tEsAJMwWe/GOfJyRmv1jcYDRVqlSWhKBQV1Hwc/ZlJLifQaTZIFuLsrtfZ2Ely1uxxc2sdeXRM2zrHnLcxB5ck0wJG0iBbS35xt/OzBzz6ZEbhLM6b60kWdhnlosMbqRK7syyf/egTtjMGYc7nRmmdmQTCvEEjFXH/g6uho6ATACHZmwovzk75V/65N/mzcZ7NN3IMBwuGrst2cYfJA5n7JxZ6eIJu1bm9cosHL5r0Hy9Vs2qFBVF9i+93S0ydBOYgzgsU5h5ks6t8/3RKKp7GLuySihfpuEPubNZYzF1inoju2T/TB78UgWA9t8b13Qjv/AF31jYY9CdspPMczmNM5g5Tc0wiEWPNyDBrvGA0MPnG197hwx/+Gb6f5rS7FKaQAxcpGBBP5UH0qBsCWqSTFmF6ecbX73yVl14qIgYRPcvFFANMb8q16ztcPmsjSFeBIJQkimt5XEnDtE26Ty9YyW8yOI2TWt/itZd2iRSd+4dnKFmLM+kpakFko1pm1L7SNXj0+JLydRF1PCNVcDk8/3Ne++Y77OYiGhc/oNsM+c1/4WskzDmjT01OL4bsr71K6MKGrHLWXyr9uoKMNWohygmMRYof3z/l7p09zk66HE89+p9eIkoeWq7AVnUV+fySuFzg7RuvYQYJqoUNANKxEklfIK1IpLb3EA87yKLKq++8zsnHn3F68IDqyj7qwOJX794h1JNUChksAybPL8gk9oHfBeDxyTlrao55+z6Z9B5GNEYLFKaWy87eTUaDOX3PZdp5hCNb2AII6QrteBYvLVL8XFlKUtKcXR4TUxLslnSsyMO9aHDStEntbZIJbOzJmFw2zTQhcv9PPuTu9Rv0XzxCFIHP5dwSCRF/5nL9lTIZJcAtGrR7Xfoff59v/uKvklgJydhtFk4P//gjXNEhv5Gk03uOltQxWz8xs+/AenaPwXuPqLx0EzmW4Xf/tz/kX/6XfhOv5/B6do/EnQ3cw4ccvPcBB4Mm6Ws14uE28e3aF8e8/ZW32CnUScRhpsGDU5PiKzXua1289SR/+IMjDiyJb157k5RTRh5lmF0mabUPmZ+eU1UWHAIXnWOenBp0cv8MoqHSnMUYjmROzzqsv3yTMJvgbNrBGdjEJAVJTvOj4zY1r8DMOuGXV/8CYAT+tIfVsJEXNo0HXQ6GT5mka0SpLmcXPpXNff7WH/6IX395ha2cz6xn0X9+RkHTceWA9mgZCBaCRiiIWO0RtfJ1FkLEdDRD9T2uX9tDTwcsPIu5N2Q01AhEm7v7r/FH7/85SlynM75agpnM5zC7h9RrqwwbJpKnYzZl6rlXqEbbxB0bVVyQjtVJqDqOPsNKBDx7cYwoXoFOt75yh+bohxjpAvlKljeNBCMloN9rU0nI3Dv3GBVz9Pt9trd/gWenLzhfbCENbVo98BPLks5sm1x+csixO6aYLZEsVDl4dMxnbZv86h3s7iX1ZA3RHXPZH1JNbzM2x5y/+CPU1BbR+vJvSgQ2OT9AnVsMRmO2i3WSjkpx0kO/fo1heRVDTJI3RDSSNNoOzy+OiGkBzw8uePutK8mr/kJEnlqMz00y4X280MCZBvSPG0jR7zNZRKREnUzBx1cc1m7tMmqY9HJVMisZ/NgSyTakMqI+QREdhNEQYSJx66t3GS2OMKYBGaPOSX+MbZuU3trn1opK/9kR0tQi0jYZ9JaA6qB/jqDM6IgiU8/m5LMPOHvmIojvcu+9f8yZ47KI8li9S65dT3M5bfP67jaePUMXZQajqzH0tm0TLebk1m9zLiU4Pm3jZ1f4g9/7PumUgRxMKUYdeu2HJBIhezfrZLMp7l80aY6uKObi/ALJj5MKt3nw6GNeNE/Zy2QJVI0wI7FWvcXbX32T4Yc2z567pKQA7+hjXqvv4+9CcWeVH55CqlJkw92gur/FJ88d8ska8XiRuDLCHTUJxDhl3UNYjeNOBmR0m0CLoWUqzMwcnni1mPWn2ZcjEHgBz5/3mFldqusFLFGj2RhyFEW0nRiFnE9MMWidniKbPqE5Ih3MkTyJuJ6nri370R1zTiqmks4YeH6IOTaZz2QETUdSZYy4wrBr4ioGa6/dYmg1UeUsM3NMXjFQY1eDGZPBEDEUSSgKw5GL2W8TM8qsFcokfZ355ZC+MyBdi2FFME24ODGbUtbAsa4yy8FBk7QO5WyO9NYmZusDDDmB1QISLoad4sXpiJypMA3AH0F+p8rcG8HYIRktS3FHFNGTKrqhEagyCzdCzNRADxlNQvKZHMm1Mp6nk1BSiMxZDPpY9oC4kmMhLmcWCpksxVKFzuyIzfV9Qn/O1v7L9M7vYxXzdDsu6aSCFmV4fNRbElcUh418BlnW8JyrNpQXSQwtEXIV/Chk0DaZRwFhqULr8Bn7t29hDyZoBYFsFuaCiJhKEgKeF2F/PqRppFPMTZlMNksts8I4VSSIQHJk/HyaWy/XmYpTpPGUuOWgxjMk0zZqLYkrpujOlzMLjhPQm08JIp9UFDAM4vRUaDVHGKaNI8XQYiHd8yNq6/sEaoCJgyDJdJpNtPTVXgvVSLJ/fZunpzaLaEpSidjYrnIjG2NmToklCriOx+Z2hVhcwsvnOO63GJo28cwVH0GMpkRel3jqGnJgslHOM70YohQlfDng/oMHFJJ1nvzRCcpRjVe34zgK5MtpJiceM2VZ0vt+RCAk+Pjjj+kFBWwtRd8L0dUkpZIGmSyLhUX3ckg8qVMpJDl5+gxNMbmmyGjxKx3Nn2ZfikBgDU+YLhyGnRZDxeN0LmIFSbz0glohx9PzJxTTGqNUgdHBAyrZNEJJx2s0sMw4J8fL8lmTDfK6QDyeIFvM0ndNlDh4qoeYdphFE+REgdXNOhN3wDzSaXePiSfTMFvg/MRchhEJlGNpxs0+WqhS04pUhAQpx6cuK8RWrnPZbXFgH5PKGRhxk3cbL8jUMlw8ucos5axEPr+NY57x9IXFwaWGaKvIiV2G9z4kR0QsLDJrG3Suy9x5+WtMZ0WSmxX21TYPP1zeLV57ldEnz7ie0/DDCfpkgjM0cB+ds7l3g5WV2zgnp0z8AcPWPV69u4cx7qFHIa1uk8TqDQBqN7+BGQREwyGDySGHoyHrlVUePrEI18eEmRv87oP73Li9hzW5ZNKYE0/lmTYuCGM1WidX6HMmE2caSyD1bTK5DAs6qIJAQVVJrmZYWasymU+pIdCPRsiJNLqYIi34ZLdWyGWXJb1Ahm+8/hp6bEB5Z5fj8zbjRYpf/vXX6NgK0d4Km2TR1DmZ+YSFOWL3G9+ie3TM4YVJ/3KJoyiTLrOUhpoQSKUrBIUqk0qXIiJTu8/EnaPmVtn8xhpOf8zdG2/gzeYIMwcjlkL9iU1XD0dj7nztFb5a0siPXJpWkxvZJLpzgW1IaPMXmIUUQi/A3FknnbLQU1ly5hht+9YX54y0OBeCxrp1xO5ejrPeIa3eM7a0VXR7hV+uvIX36Zz5PMFXr9epyQ5OWWMmuLQu52SKy+rCl7Z52r4kt/M2puXQ7j7njdfqjIZDHt37EVqsjJLOE0Uh6eIms+FnlCSHwOkxtM4JUls/0we/FIGgZ41ZK6aJZ/bptkze+sq3WYgDpnqO8lqV7qiDNw4p4KBVv4GoagT9C7be3OH5yQVK6/OMEIXEEwV6A5utSGY+tDBHPi4RU0GlVCmS2a1TePkGYaxNcZ5iMlDYSGzRMhsIwU9u8XEREj5qlCM0A7Z26zSfL5iPbXLrec78DI96DcrXMjx49MfcXa1zo7aHP5mQ4EqPQIwcKit3EYJ9njb+HEVYwz6xEQSHd97593n87Amd8xaL5jkzpYh0rYaKgSfGaC5sutEyu/S9ADkW8d69H/Pm9V1ymoQXzNi/VUSKbPY1C+o6nz2ySOlJGi9GjDsN5vkCmVINT18+DX7w0UOyCVitKnz8vM/aRp3zkzYvBjaHx+9hbI4xj5/wvcMTXl0RKdc36R+3aNoCL722StO8ynaxRAxVXhBL6CysIXY5QIvFUJMFtrbSZFN5KqJDNLE4OxtTXqsyHfdxHJnBqMdotgwqz70xv7izQqfjc3DvMddef5NnRxeEpstXVjaI5l20yjrDyzNQR6Q30gTtHgkjRiBAJC6rJl3z0RSRtLEGgUgQBIixNMWkyht37iBmRC5bNhU1z+Gn94jl0yjpKulQYdS+QNeuVHyurVzn3o/+gJdXdlnfytMfmMwXNsWNGvP5mLs3v81i1iV0Ve6dPWaejZMWBSZji93willYKxYYD22O/RWsIEPhxreYN30GL4Z4g0PymXXsxiG7M7i18xaMRC6UBf/D//471Gq7vP0Lv8Zv//H3SMVL6LJHXgnZe22Hd++f4HTuYRhJfuGbN/ne9/6Qb9z8RSTPR1k8wPSG2LMLVvMZVtMlhOhqfPyn2ZciEMihwlptlVAX+fqrNbJlgyenbbbrWQprK3RTKjOpherYZFSJyTRgspijJatcv5VBCgx+/6MP2V5dI3IjbpSKmM1zjLiC6/oMXJdcsYggpDl93sLIPGEybyBYfTxPYm56+GGKGVcf+fhsQWYnQ+jPmEYG5qWJbSkklDRzKaTb/YRaJWJw0aZUztE4skivphHQEISrlVeBm+af/OADxnOL26/fIDF4RrcxQittoimvUq5v8e4H/5BSah1vnKXdkOhfnmEIAbfySaq7m/zde3DSHpIur3Kn+otElwfoqTxRz6dsKMgxlY/vfcCtvRXCRQdRmRF4MpnNMt2pQiyTwE8sy95Pju5xc3OLt+6+SThJUqwn6YyGJIplrm9t8+HDQ/Z3tuj3xxTzJczFFDMKeLl+CzFjcHBy1YYami6aBJOgz169xEuxHE4QoEcSU3vBuX2BIhm43pTESh5reokMaKJLIb9KFF9m4E7rCfdf+NwqJzgbpXj82UOenp3hTSL+pP6QrO/Qng4oSirpfIiRWSNrNQl8g2mmjpJd8khSxSwJPcfEDRjM5xAG7G+VWFgudmtKXMoxHcO0c5+MnCR0AtzeBWq6RjkTJ5u8SgSCmqQ5e4g+tpj0YhTW1um2Bhx3D3GYsujFaZ61ORm1MbsN1t0dslsGo/GnbO398hfnrNYE3GmTHzyJ8ea1bYYNmzdv/quctf6U737wx9xYnSBacCOT4tPv3kMulLkcLIgXdxjPZjT7S/5HLLmF6Dxl3n7C5PJT4m5EceNVZlMHYWbxl29vEDg9esMLKgWduDBl9ysVpr1L1hQb37n6Jn+qD/6/9N3/T+32ay9R3sqjqTrZTIFY0sFPfJVYZoXCzgbiwznSZgq/1UJPJwn8MUEiT8dPI/kSg3ApzDgdD9EzW7hjD3dgMrAdQmJIONQqKeypj5hMMwvGTKwp69VVhr0FiuuhDVwc94pHL0gC4iyi37URI4PdaplBXMZYKEyTI26WipizJoVkleeX5ziex2wwY38ny+XoiqqaTbrYpR0W1oBcfoNkZQVjvcdCjlH0clz05pQq30CVNbb3M0QLh/0b60zNKSlJ4Pxo2befiQb9szHVtRhh8g7nocNsdkpeadOfqEwEi5PH5xQSOsHcYz49QaJEpFZxoyySsQwEic1tZpkUerXKZrrM0ekRTSvE7E+49iu3+PbqCtOj51RWVxl3ukSixFauilHIo8XKqFcdNu7Wqjw+PmBnZQU5qSNqMrqu47S7tK0hlmiQVyNKhTQb+Qy9gUW/O0BdCBy1u6TSy0GYe6ctKskkhr6CF8xoDEZooUTLGmI3LvGiAbYJi6RP01wQLTq8srYBxS3aLZlm/wKAa9kieqnCeWNKIaMxXXTxEjLxZBrJixidjpHnEYZUwp075GYCM0dCzYtYtrcMHp/b1/dv8ON7HxMmHfTMPslMgllW4IPvvUdrZGKuFDgbPqeWVdnZyLJImHz6/FOEskyUvgJUu3MorK7SmkbY2oBV1+PsvQsOpj5fW/0lThqPUX0BqSHjqEm0VBFfvMQTBVY3ChTWlhwJs2OSDwWYOogpjUyo4Z+P2aiscdkeosUMDFGmJGhs6B6u5zM4OqLbOSWWTVNOXHUyfpp9KQKBmlqjadmYrQaF+gzXG2MvEiTrHonRhF6/RTJ0iWYmQWdApBl0LB9nMaBx3ECMltFueD4gr9bouiqCKCNGAp7gkMsWCHwBXxNIOB7NwybFco75TMF2p4xsDaNSwQiuwCIvGpMo7zBoWywWCxxBolwp4XYdTpuH2PIYF4eMUWFtvcLE7WBFHs2BTaBegYWWnCdt5FHkPEM/w2IxI6SGLmv8X//4HrXtXW698jbzyZDTF+fc3F3FSKUYjy64d9IiJi+fPdmVTfLiW1wOH5NJj+h0ekwROB7NCLQFBy/O6E6m1KsVEnGRrFHHtxd4Uhw1Uug+WXZEXn/tl/FkhU+GIbbvctqbYGRjxKoiphsgOj2G8QQ5RKJSgTBUODx7jqVKdJ6O0IyrrDl3BeIkCXwF35YY2CaD6QBVFIhnaritBpHsMzN1PhtYCFKCWahizX2KaoxZa/k0uLmyglhKE2bKdK1LBGySRoaN+ibWYspEVsjmFLJajM5Ri2yuhCP5TJ0pCyXD+HOGYqM9QzHPGU3mLGSRgTXBcDUcX2E9n0K0FYT5ANUTccwJY1KM5w4PGxckwpCV7FX7OPA8btU3mPZd3JTPux8/4LR3jqPNiOc8JOeUuHpCzNggt1onVamzu75GIMO10pWcuVxI8uTyFD8m8+HZmKZSoazFsLw4F8+63PnmP4//9JzsapV33z8gOOtxY/8G18sLpnaT887nOxu8FLurBmdnXVJ6kjAmM7Z9xkfnZJUYKVWg9eIFggieUCKhG0SCxNTPoAVZnjxpcVWn/NP2pQgEreEIIeaTyRQZewvsmY+jSTQPz7l2TUFWVAJzxHg8x5r7iF4PKZ5kNvJJFXP4zhJZ1WMqSuSh6zoiCrpfZTyyiRk6A29ENLaJsmnKqQKKkKKcW0WUdRbekMifE4TWF3/TZjmPa1qsb1wnlHVq2RLZsEwnmjIyhyzCkKFjUwx9Qg9EHBb2HCkpkIxfjXyaposnuBRzBbzJnGf2mKSUpxSPcefV22RKKww7Qy4uOhQzdUq1bT77+FM0Q2A6E0h9LsM2WhgkyuuYiyZC6KCtl5kYcHExxIsU+ok0UXGVtpAgriiczC0WsRorxT0yRp5QXtJwx/YCixGC5+OEffqzF0hRnLHjUpBgfy1H17nElBXavS6zuYs/mjGWBAr5dfTiFfq8CEMERcWc+ZRjKronUcoYOK7PZDRET6RJxdMwd8kkYsxtD0FPEhciwkhDzn4+UJPJowgpGt0zPN9CCRZcWBdYsxg7t3bZDErM3DbO2CFbSRGKEeOFgeONEf2Q9OcOHLht7EVAOlNjMLOJiQvyks4kXHB5ccLG+gru3EGNfGolA0XziC0kNCkgn0iDfvV/e3TSRkhUufW1fdaSeRrlBN8uvcHJ82NOz9vEMzVuXnsNWXTZqteJ0hKBl6Fx1uX996+EQqPGBWuxLENZZGx1+Ed/8h6VokRVy7BVrdJ+8QzBiehd9ChVV4klc0SuQLxgoOgpnOmSkzIde8jJLDMWBKaB2R5SLKSZhQG+GXBx2iIMZSrVLOOWjytHxIol8mkFCYUnJ49+pg/+XKHo5/Zz+/+J/Vyh6Of2c/u5/Uz7UjwNvvPd9zlpnGNOwQxCwkBB0gLOG2dc36wThgJn/Rm5UhlNnJPOGEwmITHZw1B8vvmtDV5bf4Pv/vX/nJPDx6hhHqU1oLJeRNSTNNpDEisbdE5PsScK4XwKqoDujti/VkEBpChiag749X+wVLL9a7/zH7CSK1Bd2+b7H3zMSqWMK2bRhIheu0OoWkiKQqAZTD2bWW/GpDOkvp3H8Ib8vd/8OwD8W3/n3yOVkRFnE7xxyPNmRKgk2I9XWBQDFkLEJyctblQyWHaXzmRBKVXG96EQ11CqIn/rr/6X/Jv/4r+D7Lq4RpbpbMhi1CFRjKMGLt1Wl1ghiyB6GEqWUr1At+/x4rRL0lARZJ10Ns3/8n/89/xH//Xvo8WSCJFLSvM4umiQTKlECxXX6ZJNF1FCk+rWPuOhg5DIQCTSODlBqW4TzCT+xr97F4D/6e/+Fs5ihuNElKqbjIIZgT1jNAy5ub/GecdhHnnosk7ommxtrdI5OESPeySUgGu31rnz6l/hX/s3/juu10uoMZHJqI8Sl5jPB5SyEpcXA/S0D3MRYRGxs7dHbxxy0OyR0CUEL4EXqvy3f/Pf5n/8T75CvrLFrDklrhQZdjrkqncY2DNyyRjd44d0xkkUQ0FBY2NVIbNSoN0/IRqa+FqLv/ZbHwHwN/6b30byZ3iigK4lGM9G5NIKo/6QYBGh6DD3JPI6kIgzmQuMhzaa6xFLGfwX/9V/CsBv/et/H797yfqOhixrDJ0QTxdJxdMIwz795phMLsbESSAHcy56I26uxzAPmphGBSeU+c/+4D/kb/7t/5VI8HCtENHpMho06Y580hvriHYXfa6hxALEKERfQP+yxe7NG7z45JzmoIkYBf+U3/2kfSkCwXQ64vHzBoFRIVFIMvJ8UjGF+vYq4/kYXcsiiS6iKtDpdJmacdyZTzqpMdYjOpfLd9Sz4xht9vBnAet5jcATSU0cbC+OMIwYW0UGsxFFRaVaKZMx1vmwfUJK9ViNlfC0q8UkecUj9MFrzdmWDeR5QLfzHEOwqKZV7DBEjWfZ2L/O4ZNjZvaAsgTRVCRTW/3iHGl+wkypEFcUPEPGMk9JJTw+Gp2yEeSRsgLSXEFHYjFxKHQdElqGhWjRbvWpfS6xrmd1rBGcTxq4doCvZxm4C3Kqj79SYBIsKKUNYokkEyOGv57C0CL6zQ4xTcMPloBaXBnjTVsE0YzTsy4ZI8asPcQ3F1RKOeyDp4ysGYNGD2J5XE+gmJYYd0ao7hRfvwJCbcFAkIqUVlUsNyTwIuRiie28Rr+9wBkHoM0JVBnmPt1pyEyIMQ8SWIGP2FvyLc5f3GOvcJvz/jGylCeXzmIkRc6tDlN9QUWSSK7EmE5cGrMu/cUCJS2TSqoIbkCzvSRwffDAJNFpUihvoQo5ur0uYveI6kqB520f36ihZWWeHR7x2u01pnKao8aYlLTNpHXIRuEK5JtNWuiyzUKQ8RY2QkLGkxdMNRc1JpPVoJqIs3ADBsMmw7mGHNMx0jKKdNWzX7+xQXy9wqjxY+ZignJujYdnzxgmJigLD1mLWF+vMTQl0rEC5a00x58dsfPNN6hGJQb9JVhsjgfcfu0Vjg4+Q3HG5FfyGKGDriVJZ3JEgy7Pj8+ppxVCSWSvnOP54yec9J4zm6uo8l8AYZKxbSMoGgN3TjiTOR93SWgaSuhTTCgoroQ77OPqceKihCEL6CkDw4jhiAv6nSVYmCqWuTxxUBSVXKFCQvTwkzPc0xaVWJx0PqI3fEq6XkeJRxBK5LUYoaxxMeyTTFz1xkJ1TrFUxHrRIyNBIV9AT9VoPL/HdByxsbuLYuTJ+HmU8TnyzEIRY9junJ3qyhfnDMYLqvk01qyPPom4VlsnkcrQ6Iy4aE2oaEXWCdhKVhnmNYYxk0HUpxavIi00ip/LUNuWh6or5ESNztzFN1SGkxGlWhJNCLm8nOGl8nQth2ROATWJkRW4PO0iqwK6uMwI3c4hjrlAl+ekE3FyCZmMGmMWeXQumywaL2iNAgxXR80IpOMx5g4EoU2AQfonOiKOnsOQNcbugjk+hqrjOTLnHZeSkcEePSefDfEjUEKZIgJWAJIgIsezzD/n74RuyNxxcG0TX08xiRwEwSFTSdI8eg5ujL7jo8YN1KSEF6jIisZoNkXX4vTmS25DQqqhkyOI0ox6ArX1Hc67Jnq+zEYtycCxkWYDXo5fo5CVmfgJGudNXtotMQlEJuaVO0SiyNxaYEcmkR6STRgYqQxFWcc0LZzZAkPXyGQzDK0+1WydJ0+foxWLCMIVocxdJFBFC9NR8RWR+eCCeEogEc8gpRwa9085vhjhuCPitQyONUdwZtjOAkmwsKIlEBpPFLFnFoFt4UcKDCb4c4vLxpxYoUo6iJHUZSJJwo8ymEIXH5+pGTBRA2Lzn+3qX4pA8OT4nNKNl7EbHfSYx7VEgbPGBTulDPXEnFSsSNgOEWYzpJRINqttLIJnAAAgAElEQVRwfNJh4SQQoilzdZntqlEcL17ifuOSc9UnlXXIJZPUd5M0B2eo+pztoo8UHVK/9k2EdJHwhUmzM8HwSoyvaAT0XZ34OKKYKpGw4kgXKpGqslO9gdQbUHdA9z1E3yN7PCA4HpK5toZcypKIpC/OKaZVwkafmByRUFZwFR/LU6jUrnFjTedk2CNvjKkpqyTViEp5m+PLx0TBiOsbBXxpWe1EUkS+nMK2F+xu7dH02sw7SexKHV2fkyjWaHszEtl1Oq1jklkDTSmy98oO7UuTfHkpKFJcjUGYpnX8gnhCJ+65XNveZTCYcCGectLKs1HNMfBDSvIcUbRJGymMZBY5m0GQvC/ulskV8WZzqgmwxgsiK42v+qzlU8hziOerhMk580BkbW8DS9fZ0+KcdzvY7WdEg2Vw2tpexxMXCOkMriRiujb+QiBTXsHZzHDRaCPONOTIJTcZoBJgdkNur60wGU8wUstORtzVUDyV9omPb6TRiyGpQoiSneGrCV5fXefxPYuCmkNzJ6iSjGtAszchWS7Tm5hf3M00p9TLWRY4LMKIhTRjEhQJE0k0LcV8OoP6Dt1Bi1BPEs5ciokcoS8gSFeYnBFMcQSfV965xahp8fvf+R02C5u89Gt3+fDZC9Z2rhHfLLIjrnHeOKYzsLl++zXsMMLXU/RHSxgvk01iTSaMnAUxUWJy0ULwPObzNjNLQIrnkBGIlBiblTwpKcdl/wGlahbDdGleXk3E/jT7UgSCLDqjbhdlbDLuzjB2dsmk0iQ02E17mOY5mhYSBj2CqcbYHZHO17AsgUgTsJ2lBxeKq5yenjHtjtG314kLHonEjMPmEReByaDR4e2v3SQSBT46eZ/yxi4L1WN/LcPoUuLs2dWPFSutMhx4qIkdRq0GRVyyixYxPYJunxXPJWXMGA0uqEwXmAEomoKUK3DSO/ninGvFHT779IzE9h2OD4ZkDA0Jl2RlgealuCbU2Ky8TknUiV/TaByc0ptLnLcaRI5EPb/8qIzYBCEdRxZdZs6QiRYiZWrM0iXOpi4ZxcGey0jZDDsvvUI8V+bywRnr6QyrQYSUWVZNnh8wm3nE0hkMWUYRJSJHZD1TRDqdcGqec944JL+xSr4UQ/UFHp9Nqe8kGF62EcIr0k33RZeMliUQ+siRhKKGyEqMQW9ENJ5QWNkhsFWsMKTXuSBeLDH2fOYLhfsXDtfKS2ahNTMpJ7KIQchg0MH2wNQ3OfjgkmSxgLNIUEhkwJnizPpkRZlut4mbSVARQiRlSSjbu36DbvtT9rd2+Ljp0B7ZVFaHHA6fcTT0qTdkMjGfdG6PwWREv33Jr3zlVU4fHpLLlhlOrt7Rc0lkGFmMgwjb62NqNSZHLeKlJIlIxLJEpv0p58eXhNM5WwUVN/QpJHRE+SpYzh2dhKggTw6pzjr8pbLBk6jPd3/0mD99/Iivf+0WxsziB605ymzMzf0Vzi5brF2/iTkX8Fm2fcvlHdpHfeYXT9BrClqhyqw9QJGSfHR0TkSHV+6W6Zh9hmOLVLlC9sYenU8iGpNnjIS/ABTj7riHJ3v01RzuZIJkXlLyPF4upKnGPbzZKZsJjbmWZaLl8Y0U7e4IRwjJp1KEsaXAxXBkIhoy5Rx88vQzXn1nm9PxKc/1AVFMJ7OzTz+bIBDimNICb9jhWm0Drwv3zj/CiF+Jjk5NEcNa0Ot8THxgE3gJcpkM6/oJU9Gk0rmgOw+ZLyQqyR3OjSru+g0ErUe6sPPFOe//4AmjRZJ03GGlViOvpAmHsFEpovQnWK6IPZwwC1z8qUU8tc3wSYu4vktRHHL/c2HOhdPC6SeZzCfERYk36hs8lUQyQh57ekYyppLKVpk+O0Aulug+PoXpJXbDp5pbJYqWT4xyLIUpz7F6c/rNOb2FQzFeodedMFNl9l95k0B/xEKVWN8pUV5dwzt7gVTMMBgf4ERX26AkIyKVFJk4VfSgg+50mA59KpkbVF65S384oOfZxBSdeTzO5toaYeOMh9GCUrVAsrBk4KWSAbLnMHcCkkLEdCRge13WElU+/NM2+XqRbksl6ScoJlzyazkqhRi5iUUxITCZLzc9Pzgfs1e6hVbJ89Wqw8WLEc/7Z+RKAnt3RTIaqKFC05uQyMbQsgXGo5Bqskg1keXdJz+4uhsOnuPz9PQSWTK4GJ+j6jkmH08Z9AZksgXwRmRUk0VgMisr3K6VGA+GpH+Cj5BILBDMIbPzMXeur/DRu7/Hg25IMzznwUEce/gURdWR/WPu3r7F0XsHfH3vBuJpi2GYJJ5ZPsVymSytpMv1r34Fu/kZakZjYoVc+jb92JTNUo6J4+FkdaZhkjAWIYVzHF/AnMkU438BwMLESzeYjE3qsRRmMGYzGycrWMwHJxw8e0LSGvPaK6/z/vMLbHSMeh3r/CMqq29gBQKp3eVee89x0ByPaP4CW5B41NOZyTN6epm9bYPd2/uoisbRZy1SdZ2C6uM7SS47zyioOxjSlWadHgTk4jtISZPDhz9k//rX+XopT0yYcDaARx2FzbU92t0eT3oDJvV9igmdmQM99/KLc4rlFNV5AboOb762zkWzwY1X32YhxzizP+JwoZHL7yL6Uww/hWl2ibQShUKcheaykluyHaP8GkenT5ARSaVlKjObxcyleXpOYioRplMo3hNKsk3/SOTi8pS4f8o0FcdTVYr7GwA8++CPidVrpDWFF+YAfzRn0v4+b337V2kOAoZTkfTmK0ycY4RkAdeeUEwJhJLHTsGg3el9cTchkyacdlFDmX63i5BIkMgnEPwuzshlr5hClyIOX5yR3nuZR6ePGLfOMDse44VAMrXMUtV6ntB6zq18jZJRpzP1eTr0uPQS5HZXUGM2cXySRo6yUaWgj6ltxBDcgNGozXp5OWvwyk6Fg8cHrKpDHFlmf0vGVQ0+ah9xI1+DaozWoUP/vM1funubwI7T7McpawvsaUC6Vof/R1woNoeFx51chdYoxJQihgOHXk9FDlMYiRiuOaV2a5WF1aVgaCzsIUQOoXEFzOVX62zVdlBGIf/z3/8eQe1tZP8xpuWy/vbLrF4v0f/sQ37j9jvk/QGyYhGOf8jK1jucuSn88edA+NMHxOU1xoshT7v3UD0FczLFcyU2bu4TiDp6wuC8d4YeepTWSrizCbbYopDM0zpp/Ewf/FIEgnS8zFqqgDmYUs4mySkO4uCcZFJnqmcxtDLv3j9mqK+T1WOMhz3qq6+yCOd4gUg7Wn4IwVxlMAmIr10j45rY1gDZ0NCrLpYcQylUSYkBbmKESpZ5v8X0vE9Vy2GaEWL6ag759MUBjWDMD3/wB7wqrPBEPeVmTSddXSNrhXz4qImgT0iWdvno0e+xfXuTTw8+Q6/EeOlz6SwAr92EnkmhssF3/uQPeOXWO4ynE2yvTeaffRP3/afslNO8vHOL7/yf3+X5cY/mYMJ5f8zejSRWf6mIfO7O2K+VOfvgY+qBSK8zoHdp0x3F8ON5AnfOLLhgK6sgcMG1XJFpEENJJzGJaD55DkBO9IkrEoIqs76zw2ePTplOQ+6fX7Amx5E1C6lYwG9HHJx8SjwXJ/LbLEYZQm/A21ur/PXP76ZEKVJVhbOHH3LYb5EMNOYDheKN17GKacZynEdtj3guz0pKZdqdYZsdahmDoakwSy2BMCXvs18scl2JU07EuK9IXC9XeNK0MW2RtJFmeyeL4EekNBcltsm41cKKbLyMyIxlKf7s4JDm0SU7L7/CKPTJ1LME/RMq1+r0Yjr5tQIcPGPrziZuPEbz4IiClaAz9Yj7McatKzmvVEZgXS2QkVRGQ52XpQqWmyOuxJk6EY4/JxcDIxawdu2XmM46JKQJx41HNDvnX5xz73yMGXS5WQy4tbfKH737YxZJg1G0YNT8c775rV8i7Fm0u12INUnH4hRyW5Tu5Eg9DhiHS9xiYSucCxdsbG4gHe+wt+7x4cNHpFMpLptd1jY2sYKQ1EaVjJxl3ukhzXpso3H/+IKC8hdgwYmvr/Hkz/4e11c3qZQWIKTIXX+FR89O2d3/DSJvTL7VRvQEXD3GVirNcbuDOGvjpvYZT5bv6MB10DQNyZoiTtoIokkxt0tv7JKuZrk46JCsFdhc2WLY8jF7h+imT8cJ0CUZ/+pph+4HHJ0+xA0kpukZxsYUOxXjpNUnndao3ikRzXuMRI1v/JVf4cALmbsnrKdkbPOqInjp5W0ev9dhbPeIBTU+PTvES4mUN7a4d/iYw5PHbG0kGT49w15MOXImqNMOlUSG20mBi5WlxJQ/D3Akl616noSvETkzNjI6PaDnmrRUgaxSxpAsDLvDeeMZb33jJu0ozrOZwmS6pE+P20fkV0uIqSKfPrpgpR6n3eixfb3CrpSh1+vR7c/IJXVKW8tlI43zS7IbMUqldczjsy/uNsfn2eEnpJqfcbe4ysXxhGsvv8ygO2cvlcCc9og5Inq44OyDT1lbidNTBC5HY0q5G9jDJbZTSyeJRiGZ2jbzpslersB84rGzIhHL1EhXshwctTHUkLo6pGl1yVfzPD1OoiY1pOQY+Ids1+pEfopEmGa/LPEPvvM9/vJ//Bt8v3NMbkNn3m0jvVSjurXL5MMpucQm1qVOcDnCDi5Y2ajA4+XdJFmFRIqYvSBXr7EupqmXV9kprNLzAmLVKs3mEfHFkIk9YKw6PLp0SOY2SZhXCSWI+rTEFOrRGT98+BEzWSVMJHmnZtG/HmN6csYvvHUX+bJJ78EjFuIUvb7PpaxT36qymC+TnGykkLUERyePicUqdN0eLil6AwtfhLgaoqXi6KkMnqiyms3T+MRE1DN4NPHUK4Xun2ZfikAwH3ZxvRGClsV3AsaiQ0rKMnY0Dpp9vnW3QqiqJA2DT58dE849NLdPJpsmMgwCZXnJ7LVNJqcNehcLbMUn7oj0z18QqBrFisvsqIFwo8jGxgovPvkAOrBS30c8OyRWCPEWV6OaYjgmm3TYXSlSjHk890fczYhcdDwkppx3+iieQkp1SBfgjVqV26GKrgeMxlfCJPN4l43NDK6T4qIzwIo8Pm4+YjF9QlRK4a8LHE8HPHv3EdHYY+vWbYygx91f2kMIG2jCsszsNF5we2WdVSWOKNqUBAEjjLGyWgctx6A1prRbYdXu8/Tykl0vz0p6xvVimfm5y+hyiT7f3ipSSmV4MZlhRAKqN+f11++QtkaMPAsjW+HTd7+HOu9xN+YSSiDIMgyG9K2IuHOVNV80RxRDg1uv3aR/0mV7a4NyrcDBuU/zYsBGQURVJWaSTCwOne4YUYDpdEB73KS2uxTLOL1sUmOP3/5H77FlGGQLUxKJPDNJoPvxJ9x9ZYfn5228/hFHsQVSSuHZmU2YXmeaqHLeWQa57sxELgo8+ugBYWbBt954nYs/e5fd17/KoHMfbWLz8soql5/0+eR3H3Ot+gZPj+/xlVyBa4U8Z0+vgFDiFboDj8ZJi2I+Ioo0FmHEbNrD12OMWg/wOz1Es0WimqM97DG8NCluraOpVwInA+VVpqbN4YGCunWTmCBzZ32PzbpGx3V5/09bNCYqslBk++5fZSxMEDPv8MePGsz7IeZ0+XunCxVcZ8Zx+5xeu8dKIUSddNBmM8RkhdnE5OGfH1C4/hKVepHD3og39r/Odz7825RTCu3xFbbz0+xLEQjU2jU23a+RUC/pYfHg/od88mkGRUwxGM34J4GPeXFE9kaRgx/8Een6Lnu31uhMWrT7Era3BJ2Oj55gDXoElsXkYogjqeRrK+TiMVLcomQYvLnxJu89eMp++SVOei3Gpw+Ipi65ZA3tJxjXdaOMePyc9VqatG9RWq3SGF8Sq6YYO+e0V1WmHYnhuMO3K/uMJsfsb21y/8kRXftqeKmQvk3x5Swxctw7fcj7By/4+LlNfTWL1W8xDUBc/RrPDh/w9Vfvcnr4Q37l9dsk9AW/++MHbG4v5dNiRob6+g1urYjELy8RT1rkkykaL54gx5NMJRfts4/Jb1XJeFAtZpCFIkMpRTwdYD9pAqC5M+ZnF0RiidVIIVILlEolZpbFQg6Ye10+GTwhpySQrT5BqLJTLdM8N1nMp+zWrlqjk6nNXj6N5UGU1diqrWGaMrv7u/RnLl48Tz67oL4aY9oPmBXytEZd6uvXefLjIxx/+VzxXINPe32Ojpv0cyXsBwes7W4wbY4ZjPp89MEHzI0Zad9BsiC/VcPRknhllYXsUyttAJAu/9/svcmPZFl25vd782T2bJ7c3HyOOSMysrIys0aOTbLRTbEbbEISCJAUJECLhhpqCNKCgDaS0BstJLS00U6AFhK0EKhCd5EEq8gqVlVmVg6VQ0RGhEd4+Gxu5jaP79mbnxaeSi9A1VxnQbx/wMU979177jnf+c5319j/6D3M5QB5JfHun/0thV/bQRGf8LBVQxeyZHsyi6envLnzJhYCTiWkXEhYTi9Zjq7r/3mjQOAvkapN/NDB9WOOLl7y4ekR8+kEXxSol3QUX0UcZIiQWCQCdUFH1a8dgc0MrdhgnG2iyAVOL8a0pAIbe7cZ/uAT3ljfI58sKVZMAnWNUpTweOgjyBtULIfD0ysg9OTwnCRasf/8lHzqcxEvkAWVqqZwqeWIPRNj6yYFu8ytZoOuZuJFC+6WGuyPXpLLXnfW/qLxpXAELxdDHhTh08/OCKYn/Oa9+zzrTVmvZVGXMZtql+e5LNL5mG/86jcZLlY4R08w7A1UuUxsXOWalWoBQalTWQe7dZNnHz3C60/oOkvEOyXu/ervMphCGpwy6fTY2bhF++Ijzi8HaKFOVrsWtte8hMRVcdsu5Qc7/IPf+z06+5eMZhe87EwJipt8dnJMI2/j9BxkR0bOKWRdjTi5LkO245iLY5dqqcr+qU/uwW12TvdZtD/B8dqs3X6I/OkPMYIJm8YtrLzNYjngB6dtCmpI7sZVbte+7PKzR+8yPwh52Gpy5/YmWV1kuyAwmyy441pUrDKmrvB1u8UnTszT0ZDxKuHT0wlnl1e5pm5kUDImuBLN1i5nsxmuL3PRdZHXVNrLBeZ2lbK9BnqIkohEMfQjhY2sgS6Ov7BNLKwjZQNMu0DOVrCyGdxwwU61xFftLJLi8ngGT54+ZmOnyWTWwdIEjgZLpoJMJnu1/ZxEJE49rLrBXPRJbJl5OMLczROfLomMIo2CiBTCchyzn6qooojpwfnIIRNfIeLji2PEbIV//M9+l2HvjG5vSK1V55MPH+MEG5yNQxaXZyxGP6Oy9Wv05wIblTJPjl7woHaLTPlaR+LybJ+SWqRR1DBEnRenJySpi7WewS/K+NMxWr2IFasMlmNiq0ZWz9Kdd7k4v/hinihd0tRSSm++hTq4ZHL4AyazLj/8Ycxm8yHdtYD5qs24c8Enjz9gq9Di6Vzj93//T1iNBnhnV2SpnZ2HCPqci/0fE2kxzmBKtVTFM8oEgcSD+3cpDQcY9RKM5twt1vj0nb+hXLBo5Ktklz/3QtUvGF8KR/Dx6RPWSgH333iTZNpimoo0azZJEJC0ajzpXTCKl0hJQkGqkGoWyDoTscCiuotYuaL0WoLMqevz6HJFwS4w7C8I3IA0W+BnHz3h9Td/m2S5RJeK9M/eJbGXuH6G2ztfIVmITH8u7G0UM4yzNppepN1zeHR0TK3QwHR8gmmMGY7Yzenoyx4ad5lKMa4PGUmkKm98MU9WK3KezDjvHiH5OcYHS/6jP/gjPnj7e3z67BFbioWXTfi2adM+HCJV1tFVi82NO3iZIwryFUZQufE6J6sxln9J/2eXdMstbqwXaa5t40gLwnHCqZTS7Y3or0JE0SC0TJ6edAlEBWNnD158xKDfAVem0iiSGgKRJ/Npp41RybKzkcOdBORaLQQrj6GIjMZDnlz0sBONxWrCaHTyhW0HRy/5D/7g32Ny9IIkA4PDcxIv5HH3Pd56/T46Ju3ZklhvEGtZYmGOo2xi1wXifo7O58+5ifoaU2WAkBWRJYFqrUQsqWTyG5TtIpJpo8kpK2dMWgiQRnMyOZtu5xKlmKXcfAUAfxyS01Pee+8JaaBQMCucvjvndnGXf/Pdl3ztzjaN1KRo7zK/nGEYNbRUoLW2yVl/Rl29jggCq8RiGbEcH2KJJnq9wvmLx2zfeoVCRiSwZDxFIRIjYkXBC5Y08jqT+ZyNreYX8xyf9HDUPPsfvMPalo6ykeVv/u+foFZz3P+qiH1jB6EX4YXr5NUekqixXd/kL//q/6QmKYjZq7Q30SOUyGHj1kMeffJDFLWKqMuYVFmrhQzmHkWrQjgN+Kx9xv1miojEy0GMmKny0eXLv/MMfikcwUF/xkeRQFZRQa/hjC8oGzlkXeI0WVIsFknnMq4ssvBdZhMXu7FOUtniYiJhLa5uKV8aUq62eHR8jjNoY3kBqiBTNvJsSD79j35E7dY6N0sJ/p0mg4vnrJYexUqFx6dnNKVrjEBWc7zxehM3WpJdOZQnC4anI+r1XQpShXgywnAC7jx4i2ePjqlu13j58gh5dsDOg2uqsrDM8tXXH9CZuni1Oc3OiJN359jhFl9fa+KMPyXnGWTKJo/PQkTLZRAvCIMFd3YMrM9VjHd23uTR+9+lfXpIUV7jwPdRO4f89j1wHInWvXv0Z3OeBTN28jZPDl4SpzGnCdC6ixZdpRjVcgXsHFKzxEcnT+hPfdysSXsyZLEq0tq8RTXNMDsdcL5ykQ2DUqbOzZyJtojot6/xj3Ec8uhkQi1T5bCzz4NqHU2CbUHk3ReP2SzlyW7fYNB+zst2wML1yW3t8PGjAYdHx8jWVdhbNbNE5YjLIEemWEbK2qSSxtQZM9VkfEVnHK+QNJu9vSKF2ZzAjSAVkewmg8srlPdmaxvHiEn0AoKRxR77VMWQ8/Mhrxf2KCyBMEezVGI32+Bg0qbcyJOEMkl2gTG5rvbcrjS59NpUd+4wDxzcwGfnza+QeivSKCVXsOgNJuQyKrlakTgIcUgJJZ3oWvoQY36JMitjyRrrwgadgUNm7yatlkZd6TK4kJDNAooQ8K3f/SMM3eMvfvyUW+s7fPCjn7AcX/3/z37yQ27fu8VyGtHueySzFepNE700IFy4uMESRyqgqwLrtT3aB8doJYuB38aMVArFXwIVY0WTULIZ4mIZOZ2QihVszWLhryAAJ3WQchKqlSVNVOSKSBiKLMOI7rBHXr9SzbHMKlgLtjZaMJ3y8ScJfuyyc9NGECX6Fz1eubXD3779NhghmVVIVhQJJwvKBZWM/HM8en/BaLYg9iVEQ8WZROhyjlUvJoryLEZT/ECmczmH1ENMAoI0xZ3MmPSvyRuzqUeSTJiMFxycz8gu5pRyOvFIQrcSLiZ5NkUJZ16iUQ7RNBEt8Bk4ERfTOcbnWnOuIGEaNmfzCNMO8dSUoevzb9/5MY3GBiNZprtaYEomT7sdpOIashxgrzxGaKxV1nkJiMj4YcxotCDR8kiMKWQt7IKK63osp3MEAdREpGDZQMRiOkAq1QmJMYyf075LYSE4GHoZwcowFXRySkqQxCwFkQtnSbGwQq6uI3o+QibP2PXQ8yaVtQLeKmUB9OdzSGKkKCGMA5ZSSnc4IFkOyefrzJaXxIJAJZch8gLSjE2UOCSGBYJMuLqK5Fq7TXwr5MUowPcdhDhGX0oYoorrge9ErLWqTE979IoTZFlCWsBicEbFLqD+HPluPFsSxgGL6YJlGhMLHoqXoosCyBKr+ZKF79FsFEhcl1TLsPIDgiQgXV1jTYKV4eKkh5zZoDdd4Mo6Ly6X3Lh7g0SVqFarTKY6MS6DwQhNt4kmKZ1Zh8C3iKOrKCVKQ4a9HqGpcGvvDiePPmTY7bJh3qE/WWAVXLKNOicXbbaUhFCL8S99wmWMVlURo2up/l80vhSO4I1vfJvGmsLSHXF5fICOS5I4OB4oso5kGoxFD9ddkkYlYkFiFngIQK3VJLWvDvCs10YwcuhCzDKRWb/7K6TBmGymgLP0+eDigG57zCQYY+GSNVMGkUIhv0ay6HE2vn7gRFx1yMlFQqWOHy+xG+u4nRHII262VHoIKILOUhixvZ5hr1nkyck5cTbATK/BQm/4nOHwgMraHpWCSbFaZRpMyRtVFp0zHt64jzJo49Rs0v6Eol1jOTojY0YY5oqLgyskO9u4h9I5Rtv6Lcx8lu7sgl5P5FgqkTy7pDE3sfIa2UwZQdKRMxZmIYvnOJhmGSNzdSNMOj3OhodkboT4UhFLScgqdSYzn/W1GmLkYOc0fEFEE1R0zWB50SOcv2R+dkTDuAYLY0PnyHER00Oqa1kKloko61xMVjR2CnTaPXzRoFLV6A6GTDwTER1XjxDtIlYuZgEkepFmTiUUFVqbOziLPmpWJhAEElUln7PQBAl35bPCwMoWcchTDDMUilUG4yscpdv5FHPvNmK0IHFhpNYwbBF/6NM595CbRdzJCrvQIMRFM4pMliEbazuM5z0Onx98YZsgClTLDcJEoCysuOjOGDopRUtD0zKoBFSsHJ2TCYW8jW5Z6HZKPZ8nFa6xJkfQkTIGtzZsxsuYVVvm9t03EOQc6kYOp+vSGy1R3Alq9h7Z0CSu7nJ6/pKe34XgqnzYPxuRzlVG0RBdNNjY2yGbESnV8zi6xGQBgZhnGY1oryYUDIlxCI3tuzj+GEn+JWAW2qUGSi5l6vaYSBGysyQ1LcaLJUIoUC1ITKZ9enMfP75EMWxmEUwFj7uvbxBnrj68s8ojyCbV9a9RrUQs8kvC6ZBCocZ4OEd2Z9SMAlIkUVYVnHhFSXKRnRy71Rpd4To0fOvVJmaaxZE3WEYTrHSAbQdMhn32NprYQhUhDhHKFm4QgNTn1p7Gcmxya+ta16+hOeRba4ycOY0dm9HllHCwQjdWzBOZQbdPfi2DGXucximF+SG1ik04nWJ7GtXS1Q2shQo7N77NZuMGTT3hcnhOquhYisRKgdlsShwnuK6MZefx3SW22UTVIlZJlrJ9lQg7emsAACAASURBVLfu7pqIWZ+AC8qGwFJWGZy9T8nI4+w/YXt3B0EKKbVsvGGXOEzJaXNu1m3mqch0dF1i23zlHitN4vnkgthIkbMlIh+e9Pvk7RL2Wg1DyCFndJbdGZOpwIuDz/DSDIqooZpXDvzxxy8Y1KpEgsBi8YwkGCNYKnY+y3wyQk0KDOZjSGVm0xBz6OKuBCI/5GXbQfj8gZNVTwIGqHYFuVAiEDWWZ2MiX8SSTV48Oubu3Vc5HHfJaDkm512+fn8br7ugZTSQ5WuwcNgdoWoKw8kUS0khBT91kFWB1WJFkuqMp1PyBZuFL2EkLqEs8KJ/QhxcNx2tvAU2Kd2+R6wY6PYON2ybbFnhWadLtXKbg+PH2G6RycsppXzA299/xKvf+haHn56j21fl49W0Q0fxyRgxeVlnpmZINHCnMhUpQ8kOORvvc6tUxJ+OqOVKxNKcu/VNDj7eZxb/O8WJgL+XKvv78ffj/zfj75Iq+1JEBN/8jf+UtYxFba+Anky5dXOHO+syiR8wCwwSPc80FqhbAku3TKCAN/dRCxWIJc46K/70n7/F//iv/pyLzjlmsUjGVJiOTgmdFFHwkCUYLz2qay3GjowaLFFMjVyhgSWEdC8HiEKWf/Wv/0MA/vmf/ncspzOMSoaG4ZJJXbxgipBrYstlpsmKKMpjCysODs4oVqp4kYuSapTX9viv/sUfA/AP/+mfUChYrLzgKrz1F6iKigZEbki2WcKZ9/FmM8xyllypiOdYRHJCOW8hBBL/w3//3/DBJ0uefPwMQZTRLQnBGeAO++RKGXxZwnUdMhmbIFaZT0e4XgRGlmpJZXg6o75zkz/89x/w3f/1lIuLNp35BctExlZGnJw+p0TKSpUpWlVkQwHFpNMboks6HlnMWori+mQre/zXf/o7APyX//q7JI7Pi/0B9TWL2XKCKhmYxTy94zPicYClwlrNIFvIkavWWYtEfDtHc88gUE1+9xt7fPLJ/8XleEoSJSRRiqcZyG5CZzKgWjcJYpnlwEXNigiSTJTIyKpMRpZRrJDXHq7Tsn6HHx5/yHLscNl+xqI/5uTlEd3zMX5UQ0p8Tic95NWKnJqiySF6Y5e7u7vMEchaVfI1g//ij6/+2yfv/wnnnRQ/lfElDT3TYLYSWM5HSFpKNZ8l8JYMxjOiQKCsxmwaAqI04uLkPf7wX14Bof/ZH/4WRDG6qZGoGpP+iO31DTrDIbGU0GjWaXcdjCSllNVR7QzP2x1qisDY81kvwH/7v3yPf/Ev/xOcXgfdspBsgyhSobBJtVIlr6iEzpSV71O281xO+7RMCNUCnbNDZDVmMYv+vwfv58aXwhHkzDGqLNDrnrNRyxIMj3jS73PnVot4WUYTp7T0dUJ3xtar2/R7Q0LLIZVNfDlHPLiCad1URE9nyM6KpSMyGs4RLYlmvoho6URuwDh1Wa487lTWKOyt4TsaUhIw3t8nV7gGwrY3LKL6iumsR7m+ibTIIvoaWlYnjRZkghnj6TmyoXLvK+u8OPyMemOTciaLmQ1/bp4K0+4AKQ4g8dHDBCH0qFSKrGQZHQnTzuJnRZ48O6HpRZhWDlWxiFkROFe2HR/8jPG0g2wpjFYCUuCSRA5KssTKlVCzAom2YHw0omRbWGWNREiRxYBIGyH4V9r/ne57zCYLUklEy5jMHQ/ZLjFanvGVV28zmS+ZSQN0qqiFFZq1ohAFiIZNoWxyMX7+hW2D9oDJaEGlWkLXhkw6bYZOgDXPYcsyQsMkZxfRhDmTYY9mscIwndA+2ucnj2bcff1VAA4HIw5fjCiuN3CkmGAaUcxmmScz8HWWromnSghji1U6Zj0nMfXA0wOCUUipcFXJiCYrjk+fEU47mGpEPH1M1tHJaKCnArqhYpSrxO6Q6bDNqnfMwE6wChUstUAqX1+Yg1GJjLGO42URKwUCTBTNIpCOiEOH1SLHwumQqb1FQ9P59ut3efzu92gw5cGdLeB/BsAu1kldA8/QkBSRpVFjWdpC8DsIikMkrVNrrpinIkGyQMkIlHIlitks0nxCPnd1RLP5HUq5PDgDSjs3KO/cRSjfI1l5zDt9tpvbeMEKg5hcpU7Ye8lsGbGWqxP4QyTzl6DXYLOQMI0GaIs2Se0VYsWkUnsFobrGZHyIOs+jGzLl4jqJLOFKAdVbuxw/PUZKevjaFbLq+2Dki0jRlCDRoagTOAuOT88ottZR19dJRhMarRwZO4cFXJ7uU242qFe2qKxd1//zTp+J6GDIFq1yE72YYUrIUbCkkMsz7/aZMMe0Japlk23rJqOZi68YjGfXNdtQgSBxWM7nuGMHd+6xs9PEkfM82NvBW0bkmwZ/9ZffYeb6pJ1j6rUWgjvECw0y0hXaO7s8YadiMPAWeJLMSgpJkegtJ5C4hPkqpTQEYU4uqzILIoaTCa3GBrmMgRtdEYq89vtkNZ1lqmAbNZ6Pe3iyzPqtFp/Nx7TWtijGPvOzl+xuFjDNDMt5RE4KUUSZF8PDL2yTJBkt8UmNBXlDpLmp0516rKZdttea7D96wuVpwGz+kp0bX2MyjHADFd3O0ZBUVpMrUDWjZqjv6cxEGSEQCASf/jJByDeYLmLEYI7gTkg1h6ahEvoCZi3LYh6gENJzrrbxJ598ymA85fLwI4bDEfHFJUrWYm/3Kzgzn7JaIK9bzGYak1jHl+Gnn3yKUMzx2s4M8+L6OIy1+yTyOpfLhI1EwXFdBMvhZuUVZuEUXwJ5VSaSJC66Y/7qO++wsXGDl50LvrJ1i//XEWTsLWZaiCwbBMs5hp1hOpsx9X1sI0eSJNi6QVVP0ZMtVokPlsLt1j32z0+xiiXgfyNNVPZuvU7v6BnhKOWz0THVezXmS4e6VeTpkxckukPeEPnph8+xkykEHndurDEYLSG9xq1+0fhSOAJdjNnSQGrdIU0zXK4iso7Dd77zfcRyBm/VRxt55KuwHi+QxBH5pMzamsq0n7KcXAFYDcXncjIjThes3yrSP3RRsjXCjM7UyDFs+2yU6xx2L7AsmYPnn3CzmcebdHAJmPnXb8hPL4dkWnkCrczJYY9Ev0AVqrxzcMrewzJGUkAxyzztPkIW5uTNCUvT4mzSxbKvGzzcMEJWTaysyLI9Rpi4dI4m3N6S2Ky0qN6pESguP5R1hGlKvzemoTVw0hWFTI7R4Kp91J+cImkljEyKN/WRqjaL2GXq65Ck1LMWc0EiKciczRfIVkq9JJPLJFy8uMBVP0eyzZgocSnnFZZqzN3bTZ4vQk77I4q1DHNbwx17aI0WLy9ekuKxuVlnPBXRxRwF85qzrlgiiCn5yTlf37pPpZXDCxx6x5fMwpjqToZO+4zizQcUm5ucjQSqVZv+MmG56jI7vKrS9CYRcalOVlHQ5Sn5mUR/AkY6R9EklkJMPs4SSwKxoNFsrjNzFyw9BV8I0KZXTD7Bd5FnA3rP2ixGU8p2mdvb9/n6gzskaQ4/yZEuAtypxVY95Xw05nk6ZyQOOW8fUli/vgg8sUkk1ZDKMoHf51atgiBdktoeQXvOR49+hqqo5KplMmIBJV9hnlG5mA6YHV9HhMNAIFBs9FhA1ExycsBi7vNg51WkwhLdKJM4PhnVQpMl0tBhvog4Pp4w6vTJqFdRSqtkMj++oJyqWCWR+VHEo7ffxTItNu4a+KuYUv1N+r132LSyaKHBhXMIy5hGocDp5S9BanDcGbJ+u4bnTdDKdZJyneNKjqOhyO72bdq9KaZZIioZFAoNyvZ9vvfBu+zkU8pmGXX2DIB6eQt3eMbEDYhmIq8/3GLky7x3ErJYhKRZm8F0hlXc4jRckMuaDMZDaqmM6ujometNLpgR2VqD7iTEt01qO1tcDFdsF38DPa/SeT6EbA7PqHHoexTmDvPFGXcrm2wb1/3ompbFlRd44ZJYihGSEHfQZ3B4zOY3/gGv3nuN737/b4h6KcLSo1Ks4WctFN0gNEWM5Kp8VKvWyZbLXE4uWclZJKvIyUJHSB1EUWE4mzMaBRhyjm3TpxK7WJqA5M0omRkc5WpNeiyRq5aZazF+6DBMUiapglOQGHbOSecjXGfFw727CNUc6/YaYbQkU0wZPPuMOzeun85qHx0gjmS++maLvBSypq7IFHRm1jqdvsfW7Tc5fP97fNgdok2OyFPi9Mjlg5Ml88EJN25eHbwgSJgO+jSKFbpnLnM5wczqjGcyGWuBgoVZFliJKoogsIgWRLKAVCng9RZ03auD9+zTtykpCsEoJA1URnMJEYNRv8/2eo0fvHfK1974TcrGOnJ+hvDu24zjLKNZh6nUZnDW/cK2mSbS6QzYqpQxFQ3PPUZMzumOVjx58gkZb8GtjSrvHX2MyC5qIpEZvEqm3ORgfM1QVUKF1F+h+A7CckFQqBCRoTv0qAoxmuhhqAqngxlq6OMbIlKkg5mjuHkPo3YlqKooMr47I0qXnLw/Jl4kdC8m7N3c4ZPZgmC8Yr/XJrl4Sk1YUSi3eHD/GxSydfqdS+49uBbm/UXjS+EIKkqP5wcz7FIOwxtRSDfI3rlNTjQ4HO8yD1PCQUAmNPiz77+D7Q3YLS145ds3kaYdgsHVRohEyIZTVo7MPAg5PRnRSzSWkUDuxjcZegsKYoJHiiMKeO0zipkMRx+8zTLIUMtrX6zJtlK6syEl+wapkOPt7+6zvvdVnLaEktuhe2GStaCmvMWP/u2f0aqJfG2nTHnu0Olfc81T2UM0JKzUQGg12D/rUxCyXF6uePHZlPbFR5y1L5iOY/A1snmTWJfJ5DPIukgcXqUGqe8xmvYIArhx/x7ngUNlY42VC5l8FUnwCKwe5QQspUAcu6RpyHx2iZIsEb2rHDHwpwxHLvF6FSGTwZBlco5AUcpwXtAxswUEqY21Omd9b4Pl1MNNAjJqipUJ6D/f/8K2dueSTS/hdCTgCxNaN5p8+uwcJzJJ12z8cZen4wiztIMkpjCTyeoKRhZkoUj281eThsMxSq1FL87jy2OKGY3QgZutOqmg4PdnTOcBpCLFtSYYJfQ0YjEfQbmAmF4dvD///ne4V7nJ7k4LMWfQn8tYzTp66TYvlwb3Xv0WE1ejtfEa4/Z7RI5HId+iFChI0YiZcPSFbU5iky0KdEcnrCY97n99nfNZAYUe662Q9pOXjBZLbLkCBZ0f/PA5r//qHSIjh1W/jghlW6ec2PQmJhfjBTtbdWp7a5TWt5Cnc5bhOUW7TD2r8Oj8EkHP4oWnGJ6DWmogf64+7EtZShslvJcTCk2J9/76ZyxOfFZVCymIyckGynTK2XRIdm+dWw/uYBU32C1u8k7vkt3aLwGzsD9esvIXZNQ9fvfBN5mHFrWjBMvMMCVDqAwYHx+R72d5s3qfiTvg3rrPdH9OZEsMnv8QgGq9zmBfICsN+PDlHG3vLkZOZ2BHHA+OaO3tMvfH6NEQT1TYba7R/vB7vFHO4Rib3Nh++MWa0umCgArl05RSrkx4usB2RWpDlUcvP6TmORQLJlKhxn/+lf+Y9uI5tXhMMDxASp5+MU+lnuXF2MfHJ18tE9o1FosYceTz5IPnFLcUTvs+G80tRt4E0hgxEZCTmKwosEiuiCCZfIE0p3DLKjHoTfn133qL99oDHp97CKpOs7GDdqkSeyOydo7XKhre4/ep52t8eHhMeWsXgIvhHE2S0M0s3tIlti2+tbfJ0+NjnHGWhqlTWd/BdY9YdLqAhHf8EqGY4eTwjPb+NUYwOD9g0T7F1h5w4zd/hYPuGHt7F1VcY/2tKi+6K9KxQHEwxW6u88HZI16+fI6QBKBK9PavwtVFrkCSxOyZImk+j45PrpIyPj9kOeuTU6FVLeGvApzzC6Rbazj+GFeQWPgBhnXlLHcaOXY3KxAbPLx1m56fBd3kQrA56k9Z6BLh5IL7qwX+eZvN7dcxvAm6IhOlBh+88/EXti3mKcHgjOfDfar6jNHFEkKPZPKCtazO3o37DGYWG2tVDlZT3vj6rzAyVLJGwI0HX/tiHtne4vLylI2iicQmFVWnubnBzFthaTFrFAnDAEkwkXMZqobOx4On5PfeoOPO2fzqfQCMTIZf+dpNDjSPH3zyIdn1MkIx4mx4ipAd4LkuuhniaBZZdUrBG7DmZ5iuFCq7FaT4737L6EvhCAqbRYxRAInG6827nBycUVms6Hw2QF4BwT6vF7Kk4ZJfU/J0xZCmEfHu0SWKkaOsX5lxMpixQqQ/GjBNssiTCSsvIK5lECyNJxcvyeNwQw2YzQJcPALXI8xJKIqClLn+HKWKwcq3aaYFtqxNAkVAuowxR0tqZyOKRkpW0mltG8jtPrXNHdxVSmn9Fi9efv+LeRLBw099YjnC81eIGZUiJlEsoiBwcnjIhBg9L6BkVIyGzEqLkDIyETFW/sqTS6aFnS/hTUWC2Yh0saJRrDENYhYLj8vxEEuUSVYqGS1BmSVoepnxdIwoGQjKVa4ZqBKGYdI7GVDQy4z6h+S2b9CUbHTFwOk6aIbO2alHsJqQzReQVglxqtMeemRL11RVWy3gzQ+I4iUzZ8FbX32V7HqNSbKOm7gY9x6gHJ8xm8952NhAWr2PrCjkBYlxNCPiqicjrxYIMjIEPnYqIqkp6dRFC1yypTxiEDIfhkwWHrmMhqkYTOdT0pWNs5jQla8k5uqKSrpMKKzliHwBXc2TmBYHB58xUG18I2UYTNmWM1QbKv35nPu7Wwiah7PSUd4vAldSbIdPPkXIOJwML9j95h7D8YqNZo52X6aUKGQpoJQqzBORYDXFDZdEkcXlBEqL6+pTEoYU7TzL8ZQkEulcXmBaMqGewVIkuoenCLKPaG2hCKAWTeZmHllMcZQEZ5n//FtrXLb7YMio2RwDRgSqxFAeks2nPJ9esHtzh7qWwbhRRy3ohGmImRMo2QXSv1uO4MvhCJYn+4j+Bg93auz/6CcYgwlnXo6j7/+QX3njazxc3+O4c8jBySn7Jy+Z45GOK1RuvIUnCtiVNeAjpsMDHNFEVjN8ZcegU9bod3tIK5mdjSXf++nfsFsts3G3wiKAn77ziH+0t0v/8jG7OZfP3vk3X6zp7MWYreZNfvLhBUHfp+Xt8uTtH5NNUv54/T7LNKan+nT/4n30rMLTP7+gcC/PdGAib70OvA3AdNomX4jxggjnfEqzWUAYhJT1PL4mEYVLiqZKf7HEzMd4GZGEIeFKYJgobDev2I6JZPD84BIpUFlrlTjpDjl3fX6w30Wwc0yjhA0hZcOKKWg+f/nJE25lLM7OBmTza9StKyB0JufoDi5xehEVKyBTz/HOewfgmxw7Lo9Ozml9aJHPeGSLEh99+hhxNeVJ06cf5dhs3gBeAJAXRGiVqEkGQSyyP0mZjC5JSh6Xxwkuh+w/n/Ct/CbPTqG0cZ/x/Ltc9ifkStvkW3vwfRhJOej2qNRzmC5MllMYTzi9cMhWa1Q1CwyFRtnEzNqMu6foZAjVkJVvIidX+a+ZLCgZeYpo+LMAV50wnA358YtnlFplcprNwJ3z3nDJ5mLOXmGXZ52nSMuUYKXQ2q7D/lV59ObeDq4wxC8s6QyHZPyUmW3RtG8wOe/iCB73H7R46Ugo8xGSGjE+eEzzwW8wfHqt4tSPAkQP8gIw6NLXBLJPO7zz6AX113+VxuqCxVIid1tAR+HJR0dkszU6yopM8Razyh0AdGfO/sFzChmHSA3ZeXWL9sUzrEaJsbwio/dZJDJvPfwqy9UcuZhj4lu8/f5jthoWheK1HucvGl8KR/BP/ukfc/Y8ix+1GMQ2v3djj7/6i+/xG80t0tMR00YNwVvxB7/1bY7PPsWObfJ2iY+P+3SigIVwJUxSztusl3eZ7JQYi11acoHWjTscTB0GnSf8zv1dvEAgCQvcemWLspmjLCmU7TIvj05xxtf02WopS/f4JaFc4fhwiBg7VBWT1cszXswfMYtmZJo1DAlCb8GNrXUOxyEfjIf8wc41VXkRgC/7hGmIkBG4f+cOZ087ZMIc7XBBYou0DBFd8mmYFkpWobuY43g+OTEC/3OpdkPnZfuQF+cd5j8awNYr5DbXmZ4vmKYpB7M5+2HIpqTyxp0KfueM/cmSQiZLJS2w8fmbK2XT4ug0IZ0NObgcknE2UNQQTc/wLNRZLld0iOg+ekK2abJMIpzxglLQZmEVSTPVL2wr2AbvPe7wh7/zNbY3iwiyhCxYaFs3UIdLnrXnvPLmHYanHyC5I9RoQDGKUTaL+Pk6unkVrgZ+Dkt3iVYh4mrA7PCYkl0iUDSyxgZrGR/ftFHdJWM9QXEjhocnxEUJz7W+aDor3m1Qz9msljKxl9C8WWUZeKxRZ+aOGfsagizw6t0Gw3ddTmdnvJKtMJl3qDc0VvF1Hu3ELpPlkNdvFfnor84RtrZp2C1yQZ5cs0W9E7BT2yVOBM6GPUZSFn2txmp8RrZ1XX1aRCryyqWypuN1R6wWHvPiOh+1h6yn73Pq9aiuvcJ83qHcekAsmuyfj3hFLtAfC7Tfv+p/cBY9knCBUa3ya2/UeHewj1tc42LYY7XsEiwSipsVHKos4gsmqxdo8n0S3+HofMnt2c892vELxpfCETQ3tln66/zv/8eHfLNa5Kk1Rmz3aGxtIAUF0sinvNZiGC9xq+uMR0P+8scfMGm8zj/7J99EOL4K59KTQyYNm5Gikl/7Kk8ev6B3eYi91iBbbtE5b6NYNhmzRBQk5CQT3x2hlKuU5jGWOvtiTUapwfsvFhwc9TDytynXKnz08T6vvfUWDgpiMGZm6bx696s4eZm//pvvc6jCZDkG7RpZ14KQIFUZdAZYks7AmxCYFv2xQ+nmHvPpJWneRNUtJEtipsGi4yAbErKh0f/cOXnuCk8KUC2F6sYuR90hM1GgVK6ixgq1+ha+O8cK5vT755TFgKV7TnnrLnd3axBcEZNSs4RUS1EMjd1aDi2RSJIib3/wDOPhNynt7jAf9ajeKjE4fI9M4JA3U+oVgcrtPYLounnlp5+9z5uv3+S1nU0my4S5NaW8ViBdBjhmAdnvYicSCBJB+1Mkw6W8tkZelHj34An17SupssHMwU373HtlG2egImZsYjdlO9tCjwKCRMdMVywJENun1LNltO0MT/tzxMWcl0dXYqEzLyLIeKSJhRQL+AuXSknkwcY6T/o9Nm5VGRz38ZbnWLZJRo14OZ5Sk/IsvAA/+rnDIi8oSTM2MzWCvQJFPU8xMDEDE3Ui4ntjJs8HeLJNUW2AGGHkbATd49nRNY4irrfYKNzi5NF7mK++yeL8mO9c9Nj65pusnDbVzB71tXWyN3foDE5Rc002ygVcVeBs3GNn5wEAo+GIirbCO3ORd/bwxRFaa4tqI8IYvMuNhy7u2MBbLMmxhak3WVMLdAUPJY5A+SXgEWzufJNO5FN/4ya+E/FuP2b33g5Rq0o/rKHIGotwybyfJbum8ng2Z/s3/oD0+IT2xQvevHv1sYLJY9xiCVmp0R84iGs1jNGU1fKCXm+GmehMo4iL4wGyumLZ+4QNu44uTogrMYp03Vk3GM84jJ/TemsPdzTjneUC/5bGR8U5RaPCrC9hVRTe91L6vSmZO2vcy4Rctjts3d79Yp75eIqDgG6aFOwqqSCTKWZAmNBZPqLUKrMM59jVGp1em3AeEac2nquhpgv4nJPgyUu27teoLIsso0t293ZY6tB3IyTVIBFjFisRw1wjM5fJiwE3f+MhjNtImRXh4qpqEFk2dsNl+41vo7onDE+OWN82WNu8zemqx42tMrNlGQUBr9hBF1J2b71CzmmTf/VbfHoeA/8TAG984zVqXkQvEpF0AW8xYN6FyWCOtF6gP3zB4mROTZvi+lOCQCIniUSBhxSsmHWvOBJCa431OEZTYIjMq69uE3gKopjhZqWOIk1ZhDGhIDMdLpmEPpLmUdvc4KU8h+SKI2HmszwdTrCVAkkqE496HJ332b2zQzFn87Pv/YA7d+4jzzsEaoOyZdAfjnA8j3kyI15cR4SfHVyizg+YLIZYgkxZnHPy9CWv77zJ9MyhbpkM9F1yVR3zZEGuITBq2fhOGfHyurIymEMSj2kUdI4nC9S1TW5bBbrHB+hxBsso0J1dwkilc3aAUYNxuGBt52sYqs5yfrUm3x1yMJmSuxgieyrnp88IN7ZobdfZevXXsW9UMOQKlz/5mNPjETlR5Z2/fZeH93+ds2cfMXqyzz/kj/6dZ/BL4Qiy5Qry8VN+/x9tIKlVzv76iPY45cliQrlVwFxGVG7u8uJwQTUZMs8knAUTbn5jnVRc8KJ3pRo8n3SR0yajSOPxqYtghUzjlFa1TtcFv1lidnDKXLJR5RXN1ms4vQ6rOCEfuFjpdf13Z6+Jdf6MoeQhNm5zfNRBL2ZZLzfwNQd1LSFXyfOjx5+ysRYzjCfktnXurxWJ0+vyYZDoqO4cQ5awbB3TyuImIu1hn4yaoNaKULQIApdcMYPcGxNYFhPHwXdSavmrTX5+fkG+oFMtZ6hrNdbWb3ExP6ch5pHtKgQJqwE0bAUl0Nko32U8PSOVS4xGHqvV562683PEcY83fvsOih/AnoDrZ7HdKa+98W3ygYAiRmS6DpU3fpNcscjYXaImd9lfJXQvrjf5a6+8Qrzf5fxyRlNPkaQ8l/0eRllksxLRzYhMuhfMpwtevb3NaBSwcC9JkxW1vR3GF58Dc+fnpPkp4vmUuqnzac9jQ7dpbtnMakXSgy7jYMVoOARCgprBRuMmB5+dsEgyRNmrVGxz5y5P3p8zShXkJMSfzTAyOZ5/dER1XWOdlO1CwvC0j5qu+NmTIVapiaAFrIIeD25fpwaHzw544+vrjN0VGxs7KMGKO3tbfPrBY6pqi58edRm/fJ9v//pDzi/72Cub2BSJohrN6nVEuD8e81qlzNRTiUMfLUkYukvsco3C3iYnxyesEp3d7GtYt1ooVpZXcgmur7AchCxKV/Tp7eomqXCT0aXDfCyRU27QOQ45PjrhW3/8kCCps3ri0JQrROEn5AAAIABJREFUvPfxAd5qSbH8Fc6fHyJrJtWbd/7OM/ilcATu1KW5t06Yjjntr4hf0dhI9rBWGh8dniNbKlvykuShwKXnEmgyPecFoycBS1OlWrvaCH4yQPBCPn70I5o3tsmvG8wXMulqxmQ+586dDeR6i/FsQrNkEA8vMKZHkCuzbsrgXTPCbLtA64bGZ/0Bf/20j5pmyWdy/PTpX2OZNpl6AWX6BNGa4K9ifvWbb3H2+G/phWO+8rVfv54ntQGDrKmQOCGqMiEIluQyIYYSwaKPnCropsTKWRDIApauk7gzVtGC2eRKfWkynbK+uYfjDrmzsY2szdiu5GgaBXpuDKpArrpJOhtgyzbxaojfPWPhJPiiTfy59v945nJn/QY/+/gZdzfqaKKFk6xIFZ0oDBjP5xRMmbHgsr5eJI0SxGFIxxtzkWax125/Ydt4ccnOK9uopopk5ZlMumh6wIQR6skhwiLH6SfHfO3+Lv3+CFEIyNbqqFHIp/tPmZpX2+941KOmhkzQMfQikhkzz4m4c0i9LoaqMfZWjFMwFAkCncHLGU7hJqku4ARXYe+aXmRUUzgdTZh4MSlNqrrMqzfe5EXviDwVtF6K4ZoU8xZtoU23P+HVRoYMGlF0zcdPFm0G5y4PGnXqtTKXB/voZp9MS2d3PU8SumTNPJKw4g9ee41/88GPCb0yY29F5Cy+mEczdRxHRvESymstOqM5Nx7uMem2OTsd0NjeQUwS+hkBeaWzWoCvxEi6gWLZGFxVICYXY/JWmd5lQKXs87BcZf7uOwyHHY7XLBpdlcBTGc9Ttna+yWqy+n/Ye7Nf27LrvO+3+nb37en7299bdauKxaLYVERJNm3YMhIBshEgARLnwUCMPCSAbaQ38mAYcRAESaC0sBAkcmBHkBEhdiSRosgiq1j9vXXb07f77L7fa+3VrzycUh0+MHxMSjDHHzCxxlprjjnGmN/4PtxkRNXUMPHITv8MqCH/6LP3kHWNxVsLrC2J7Nz+CmcXx9xbqJM7KTOedHj/7ITtnIwziiiaOc4vXBJBpLC8gvw5nVfFMJHTDksZiRvri4hzl+GgS1rY5tXlhOj0kpuZDF4os5rV8KcNFsomRjqj4wTI7jUN18qtFR7MOiwuBEzvL9Hvzhm4PjkT9IKAK44p6BleXy+hJQ6XF+/iySNytQWeT68zCyEKGZ61EfMFKrUSRmzTGzoksxgnDVkrZxiPZxTyFVInJnUkhhMXQ1RIfAWCq5rcyNdw3YjZaEKYygzHLr1ugJgVCAQZ3U4ZjHqE7RGOETNzpgzbQwKhyCwIcJ2r+6NuWqUUFzl58S4TKaC2VuGgNebsost2YCMqfaQwpBYUef9lkyQMmQx6yFR5ptSYRddsuNORSVAvoK6uc9xpIeY3GfkD9NDnhdvheNij/uY2exOfncIdpP4uctZiMgtYWCmynSvwz/5PuBwNmC4sMV/SaDgTLFmFWGacnoKkUUjBqOjUVtbpXY44612wVKrSV2J6fZfoc/R05Cnc37zJZfcpwmRK4kxJxSrdtE/GTyioJfJeldFwymScUpY2GPUbTFMfIRizurD2hW93Xt8mX9GYK3lsQrYKBkVsyqtF9vZeIGZktqWESarz9PERhXqNebGOFCX43nUgEPonuI5CYb1Kf94kNDROZyFRKtETRpQkDUXJ0XH71KoFAmkMpkbXuQSxT7t7tYGXtSKhkGV7qUa9XkUQI964lWE6n5BMTArTe1SzeU67+5QMjSDqMY81SkKK7qvg9X7uHvxSBILEXCdQpuxezNAzMZrvMnMmtB2XbF2EfMxN22b34yPKVZNxq0OnecHWrWWyUUSSXJ0I7bNTCiWbry8tMLo4xA/hjmIhCCmjJCbRIyx6RHKEPZ6xtVoliaYMeqcMjw7I6df3v7tPz6nVN3j79fskWoHL0QApGNJrhJw7A/KKzWzk4s58lGSOc9ElnPfIOBnEy+sfoZKpo5Z1cpksc3dG9/kRg6mHkbGo5Bdxeg7FYpWgOUYTcyhKSGL5zCYBN9fXmX0eyAsrd3CjMb4+4/nRGe40IFAsgvaEQFCZuUMURWPBMjm/GBPMfQzDJPVFpuM5wufDS3p+kWG+SO/UwDufsaPOCQyNk9klpx9FeOGQSJJYsIpoYUhG1rk866NJPpFhMrKu6dyEXIH9YZPcooYoR6hhQLdzgir45FYLjFtDcppGoajysn3M4HzMzY0dJqnIXksm710Biu68ehNj2WYeJ2hFiUnkIBseQaRjiCrDdMJwBrZUxc0ESE6JgWUjJQYVy6SvXv3Gqlnk6HBIxs7hezKGUGbeSBlbbYaTNt+8dY+9D56zuFxD1FTUWGV1+QGCMEVRaiwa+S98K+kelfIKehTxo0ePuL21gRjNWKnUGUUmWirwtHXGm6/coSTWCQo2J90Yw45QlOteg102WVyq40VjQiFGkj0WC2XGnsLO6i1MIWIsBeiSxLA3wQkVht0hpiIRz+eo2tUz9WcDsmWNzVyWXreN66cML0PGoxF+OiAf1RmOPyIVGmSXtzGlLLcWVtl79ClGLmXq/xnQNfjgw4/JV6uYmQRbV+jOZ8iyh2ZsMVBU9JyJpvZZfrCN4sfomSzrmzcQYpl2Z8zBp58BkMwC3JMRaZCjlLNoDTooqsf8vE/qTKjX6liGRuhO0Awb//CYfv+C1Pcxpz79s2upqn/6z37M7VfvMeico1s5vMRBUTTWbjyg3RzQm54y91Jkw8ZxYzQzR8Gq46cxP3pv74t1hvMRftInms2xdAFLVxAUgSSOGU0GZLMF0umEesXESkVcMSSVQgxLwA0mmKWrE7jdniGYKZ4j4ccCo/kM2fLI6WXwYyQ3QlVC9o9P8FPwvD5Fq4aklFHtZcLpFfvOxJ2RdD2kch437fL0PMEumMj5IouVJYbdmNjzkCKfYSLTHfexS1nCVEExIFe4psUuV2RUWeRg7zOYpmQqBlgaR5cHVMUS7eYIbRKx8+Z99j54iqVmefeTT6jVLTJZHSt/5dvy+g3UQsJsdkE0l9Eli9AdMYknFPQytUKd1BfoRyGCmCXJiDRdn0kYk2gF/pRbZ9R00byQtXKZNStLMpY5DkZEoYhs1viT93YRxIgwvMQLQiaxwWpNJF/xsO08rZ+SPLtz+yGRnmHqWCy/nkNOFGR8Ds8bRE5IM26zs7HAnBlWaRFXCtFokpVtAuu6Q+9Gcx7tHxN5c3qXx7yyVuJZbx9/7DAcjhDlCFnRsbU2qWGBJHNyeUAYW+T1Ik5y1VAVRY+Lw09QN77GPAVbL7BaneFVa1h2npuLNYKkztFBgDgYU1wpMDt4ST6dkwzGVFeuCXV/lv2CoegX9gv7F8S+9AxF//V//jt0+pcIsopqaCjCHHfYx5QlXB+CNMawa8hCRBqFTIOIWDEwDBWvNcLIFfm7f+9v8NHv/mPc0SWpZuInNr12E9ebUctaeLFBaApk0Oj1u+TLVTzTYNLqUpACymUbU1N466/+dQD+79/+84y7MHJDRFnFyq7w5LBLZaGI402JZzJL9VUabY+Z20cOpty+m8Gf+1yevuQ//a0nAPyT9/4BqikSRgHiJCFKBRI3pXV+gWhrpJKJaWmUczZzZ06lqDHujcmZFrIi8GzvJX/z3/qHNP6n3+Hxs0OydobG81N6oY6ZLTD2RURBpdFv4LVCsoTUl0wsW6MsuYiDGTtff5PIDLj9d/4Gf/vf+W0MyyBwxtg5m5OjPQJZopLPIWgwaA/IZ2o4SY4iPqKqIhgRlhRzuneOO9f57d//2wD8B//+G2ytP8Qdt9FLN+gODpl25ySaTLVQwXcDxqNTcB3W12qslfJ88PgFWVvDax5zdNDjf3wn5ff/1wy5pTt4wzF2WOFs6iNoK7w43uVGuUKoVPEdGTOrMppPYN7E1GKWKhqm7NM4eJ+/9nfgv/ivdnFmDaazGbFiMnMTMorI+cVLBrMpt7ZWiNA4G4dUixUMJaI3FajaIcQzbE3l7//d3wDgnf/kz3HeiJD6AuPokkXzlzkSUtZyKvvtJ/jnCfHaXTZM2L/4lJ3yGm98rUqjMUSxFN7+z/5nAP7Cv/vX8aKAip4hdAIK5UUURaacy5KGLq3OiCRxuXmnRnckkMQiqpLy2dmEQJMQjTzf/Q//Fqe/+++x9+Q5gashzUcUlpYY93IghyALvPf9H7JZ2mTt4QpCFqzLCWtb60RhxDgccdw8/Bk779q+FIEgSAMiYiTRJ6vr+I6LoaQY4pxIAkkI8GYCpiESRR66qhDIIEZzbCsl+Fwx9vxoj0mvj6OZhFqezmBC1gJxPGDqiIi2wVkgMJ2MySYKiTwgmbtcjtq8Ji2R2td81jPXxFct/LGPKUnkjXVSBHx5if74GH9iIKsyTqxTr2wxONllNtSpZEqM1BFwFQiCyMUbwNRPcS86FPIVbFknX10kiVNkrY4gTZj1fcIQmpGPKVm4QooaOFRyV/JZnc6cz54fsrp9Az9TRIw0MBWGvTmxGCHmsoRTBaGg0lNA1XyKlRpHow8YjppUq1ciMJlKGUt3GU37OH5EtZaj2R1imQa5vIIRw6h/iS+NEXWbvJnQjxJq9RyDUwnlp6SzTK2K3/MJpQLKXCHxioTxGD3JkPhF5kEC0xFuoNBuaSyWqmS0EdNRj5xQxTRjYIBo30GUl5jNTCa+hi4uIgqb6ChXLNJejSD2EIchUVRCQkXLyhi2QkmY0pKfAg4XF6ck8y59V2DkjxhMI4pLOTw3RDFMJl7KKPJpDGbEgoQcThjOVSZtj4ziMRSvBU4OTmPkUo6imiXplBGyBYq+hpctYnktmEGpWENWJO4vhsySMRO3CtEUz71Wg7JLVcpiiKkq5GONKIqZDBrIhExGI3JehKiD4jlUjTx+oFCuZ5mGCq1UIIyvsC0T32cagK6KjJ0U4XyAmMvhBjJiGrNYzzMJM3TmKnacULCWKRYKvHzxnMl8hhL/GZA8i4MeluoynzWZpVmsbI6p4zGJHPrTlFzeplhWcFyPhfUSaQitVhtFBoQUQ/h8eKWSZf/sgInrImgBLK0ym02IpSHFmkE3mhOFIpXlGs6sj60KTESVRDdwJQ3Num4WnbXLSEqWgTdn5PVwUxfZKDCfikT5JRrzKb2xw/3VAu6wj60v0+n6BG2djdJD4I8AaI5lDMHCVFWmkoc7iTAyEtE0obq4zmF7RrZc5UZe4XzQYxBGtB2fcWPATtkiFq5q8oGXI7fxNr6mkM/P6XYu2O11UMsLOJ0J/kBkLGbR3D5KGuJLFd656DNILAZnPtvWVWOuvLJNVhmhDHY5O3xOcWmHcqlCMPRpjBo0o5h8tUQ+kLm7s0G9JvLydMCgc0mcVakb10NHC6U1Zo7EzPGoLJXJCTXOQhfTrhI6PQ4/3WX95g6vra2iSClmIcPirQpBHJKe9ShyCPwBcbrDUTNkGqwiTkIKpWWmuzEF+xtMhzOet0PEwKWqwPqWjZS7y8jx6Dy95NcfvoltjIA/ou3M+Ownn2EX19GzJdL6Aq00oFYSqJRsjlpt5u4AX9RRkUijmM7JBcbKIi+7Izar19//3ad9bt25iW8p7DqfoE19TK3MpHFCmupQsPjku095eDdDNHdgqtET2jD0yaTXCifL9x9SqeRJT87oH/eI25e0Hn+EVl+D2Ri3MyIVRfL+HWJJIBBFwrzJK/c3WVYsPnx6NbfwT//wHLGos2nVQZb59MU+hj4nMGT60wml5QWkWOaTDz+g4kV0FxZ5770PsRYNxpd9Frb+DPARzFvnLK3k6QUBXjBADANEbYZm5JAFB3tlCWfcw8gKTEeX6KqB73ssrqwx77s4/lWTx4kjNr/+KzSGXbKZIr4oEvsqx6eg5038+SVWVgVVot9zqW9sI0cin37WZzVNEfzrbu/W+mtcuDJe55SFG1m60xC7FnFy+IIeDhlLQnAlFFUDKctA8amuP2Dy8oBxeP1aT/caVCrLBKLAYmadaTBlc+MW036Aouts10zGTovLWcgYHSIFO4Whn3B05rOxdYXtz+RtFKlKrqCTN+aMh/ssly3SwGF5O0f/4hL38hnZGzlWt+8TCFlu2Fne2Z2TW7uFVbjKLPKqTC4WyGSydJR9HG+MEs1RVYutzYe0Tp/x4rzFn/vmV9C1GbNhi3gWsli1sQo1JOkaNTmOIywrRz8y2DsesVW5g2zOOd7rMjwZsH8QUFhb548/6/LGwy3mjXOyosxRo4vhwOhzye/j4zH1jQVGus2Nh3d49uSQhbsbqIHBx+82cZwe1ZU8dqbEu4/fZ/3eK6xWJV62Iv7waYOdhQfAH9E4vaC4c4dAtCjkddrxlJOTNpOshlhfwlPHVOwlalMHbzgm8ByWCjpG6LNaKUN03SzcqjyEYo3xUOWt+9+k0RhhZnwWpBpe28WVmmRv6tzdMmgfajQFi41SjZHnQ3jNBrSVzaK6PmZqIEsaT1702THWOXr07Ir1aOQgVot89L3HbH01i6qquI0u1QUTlAx55eqZqvIqrY5HMx/x2uoaIgLudIwgeeTVJQp1mXZjzGt3VijkszjTPAV8wiRm4XadaXjNtfGz7EsRCAiHWLpNI40JdBWjoDMbhEiKyowJXvOI2sIKqhyg+C6K5FKrRcjSCIQRpn11au7uXXCuX4CSkMyGON4MgYQxJoN4huudkhEtquUs2dIK+04PzTMRFsqcznssJdcQ406zx8vhnKbvo6Ul4nyTl41nJHWDQsYhHM0o3lzgk9MfUTe2UBMLy/BwcyrT+Bq8IaZzjvdfUi+skV8sk9PznLVCmkeHFIoFlAg2bt9kMBgziPKEvTZW6LMoFznrnXLw/KrskUIdPfBpvTxn/Y08qRKzsSDz0UGDaOgSiDNe+7rGxdkTutI6ppLhcuiiiAazscvj46t11OkExVBIZZ2VldeIMzbddp8ozvPxeZvLocHmV19nbtu8nF+geiGZYkAuk0OWMhyOr69YzcoSra5DeXEBfybjzEQ0oczGikznOGR1Uad36TMF9pp9NvIiUbFIbTng4vkBl/0rRqDFWGY07DCTK5w7Gmalwo8PTxhfDgkSh8jvs7Jc57R/yYkoI5syyRxWH2wTnAz47MUVY3BG1/EUBSmYIQcgumMymSzDcY/M/Iiy6dPqeBSzSySWx2QwxtCyEBr0RlM88XqOYm3e4uJ0gX53wNa9HZZqEeOBz6x5gbko8snTM1YkiSftDC0nZm3xAZmshTDIM+tfl5jbFQun63HZPuX4Rx/it5sk5RwL5iLOpUjUVRg3WqSqhtDxmGge+eUcs/M+9799k4v2BgCrokwwHdKLMnxy+ZJCxsHMJIhuwPu9Z6zk19jff0b5/gYX3R6quMxieQ0GbU6enKAuvf5zt+CXIhCIwhxroUw4ahJqGVpjh6la4Hzoo+Q3GA0d+pOAr9/fYHgRowspsjVh2m1jRTHDyVVNtnuyh31zHS9VOTkfI1dtQkmlfmsLd96huF7ECao8757jDyNWdBkjaLBUyFNUbQaN64aKm8zIZiNiLWUwHpCtTMgsz3CipwTSlBuv36a2NGfpdpXjvQ5atMNo2iS/VMRvdq+dm45YLS1QslUG3R4L2/e4cCPacw3JqtO/HNI/nHN0OMCwL1lfqZGeB5TzGnFJIbd4Vdt/fNRgJmR4/d59JGtMYW2N3/v9/xaKK9x4cJcgb5GkKZYmg+DgDw6p6jlWShUE3WZpYRn+D+jHJvJ8QuKETHsX5OIcRkbgwokYiKv0xp+Sc0ecHJ1RiTrU8jqbpk0aBDjDC/Jr15OVp4dnJElAMpywuXgXu2Iw9kSmnQrF/JS9w8eUFteZ9F381OBlbxd/5JKTHcKwx9LmMvAhtl0iX0pZLdocdk9wvBb3fuUW3/39fdKkTRzOGKpNZlmZIIzQa3PKukb7+IC8NmbkXZGgjkZzFLdNef0ejz58n/zWGne283Q7Ib6eI1cKMKUmR8d75ItFTsY+FStm0jpE0DLcuH2dPo8ig6papPrtNzjstWg3j3H9A9KsgnM4YPPVPBYWWUGmc3FBrvyrJL0pS4sb/OCj975YJyuZWMUiP7x4h8JGHrd9zvmzj7m9soO1eIO1zTvsnn3K8STkyR//c5Yf3KAt9XCE1/AeNRGNK9yGl19G6sx5bfUOjcEhUabDJ5e7RKKAk1doRAPe+M6f40d7z/hqQaHRH7DgLpGTyoTpkPBz8tr/N/tSBIKFcomj/RPkzCKuZzEkwBWr9PSQ8cUEw15AikX++ccHVAWRUjmDNIkp+TEF3WehfPWypn6fxomKsnWb0nqeyWiMmtHY//iIaklnPDpBlHuERydEgoyzUCcjeQwHe/QTi8S9nj6LkzLrZZViPGXv7BMytzL05yr3tpdw0y7h+JgfPnpMMft11m+UefLRjIpYomYLpPnrUd2Hr+9Qdw2O2kMEIYdm6Hz24fsIyiZpy6G0sMbLS4/pdMb9ok3rsovtjwniEnqhhiReweZO5lMMw6QXjvnB939APuszS3Ps3HuDviWxdLNE77MDvvGdX+Un7+zTGrf45tfe4ocfNTGULJ3RFaAkmQ0wSkNK5TmjrooXJjwfJ+y5fXYPuyzducNlL2Axa+IEMplcgcd/8I84nQTkl7YpSddz7RvVPAPP4dOXDfzU4uHGPTKZMu3LJr/85pts5ZfYHZ5SWnFR9ZiCkEFeKxCNhuhJBSm5QoSmqkHBtImmTXZySzRqq3w47CBVb7K4tMyKlmG/P6LjJsgZHcOcE8kGGSmkWioRu1cZWK5SYDjc4+RCRaplwDlGk3XS2R6Sv4ncPeaX79/gI+8FZtnmxv27PPuTd7m1atEPu3iz6/v/D85i/oIhUDIDjl48pyP1aCYxa6sqUWHOR5LAefuUv7j0S2x++yu0HR/peYSzaRNmr/soLdfDd2M60ZSjR4/QAzDEFcoP32Y2CDiLE+ZrG0wPjrkII5599Jiv7fwK63mTxJDQRlelQdHykSWJ5qd/TLSSx9CWObj4MXLBwriVRV7W+OPGCVJlnaEtoTsix4dTYj9Br9awrGv6tJ9lX4pAMA9d5Pwinqcz7Pv4xTwXvkpvruJlKowmY+qqhSdquKnDeKyzqFZRU5GSFiCnIwCe9HxM02Gpe87g/BiMDKY/p6SoHH20x/3tIs6oTTBwuRyck8mUacgOkafQPj9HyVy/rP55EzdS+ejykPWbKVrV5m5mifVak8AscP6ow1dvf4u9RsRokkXzVHRbYRSAml34Yp2yqdM4Pebi8IKtB99m92yX8tIqj59FfPb8BbmdGNWZ8K2Hr0M0QfI8zIpORolRIpla5aq2X8oUee/wBIl9wkyJkTnj7X/lW/jVOoPIo/TmfZSKTL/v49sexZ0FvEzCVsHkuDvBrlzViI8v++weHfBW4QI7q+AlFpe7u1xoECgiF4FH/OEjQkvBlgzaZZM0jFlTJVBz7PwpsQHQGl3iGxqVVQ2hrPDey08wzCqinxIKFSQ/4f33X7L4l2xmasDSZp6PP/0urxZrrGyvM/pcWXnZFJl35rx7/gnLt3U+8qYcuDAeg2Op2IUa+88mDOZz3vqVDSwrZP/RLgvzPkGwysbKTQACO4/t6dTyPp5kMExNvrmR43EQko5+SLWkEA981HDKwct3qN14wOnpj8nf/iXyhTL25r0vfNuRVMrVNkcfD3jr/jpSPKZ043XiwoiGssTiSoUVp4pyVsUfnmE8ttHvLzJpXDCcXyNLI+eCveMOba+Ptb1Nbtwjs16nbUUIqkyg6Zh2jre/dQvpRxk6zWOKpsy806ZUt/jke38MgDSOOe22CMdn+JrBzqbH29/5TcSdFd6dtKEyQaz6xE2dqZ+Qy9jMzh3uFjO8ON+nv3v9TD/LvhSBYOBc4qUZuuIyimXREwsEsY1oLOBqOcprEEcjnOEpglVgPHIwTJnQl0gDl3X76mQxaissZbMY85DVrM1eZ4g/UZklEklQZf9jWKgtIYUar9aqmKMhS5tVumZIGkvI0vVJLhpVPt3dxX6wxqPGEe2XHb7ytSp6dQtJmuB7XSwtYfPWXbxmgCPISJ6LEMmM2sdfrCMnMeVqhXptCZQColDlk+9+ipB/i5VbD6ls3qOYiZkOD4mGEVLQQo3OEE0Bw+vzonV1pXV23qZzfsRGzaR3dkppI8vjcZeVzR3SVObgsMNJM2S+36c80FlUUo73GmhhhhcvX/LN1avZ/3jY5OJoj/TNHPP2C+KFBcLhARktw1/99j2eHD9mYTVifbVE0msSOiLdKOLGr71NtVClNfgpgk9nxJARcsamuOjidyVMTUSxCnzypE9m7PLKSoGDJz0SZYL36hJbOyqq5yKlLvLnDcwXpw1US+XO3RucyhbtgwFbd+7xYhTw8lBhubjJm9/eYJgMGXgJ7v4PGRztsXp7mZVUpPH0ChFq2Etogwz6pMdWVsSvS3z6h79L/c42E0dhv/mce8kmb92usTDS+PjJJ/z6r/86fucpgeIw7F9/f8/TePRiwNprr/J77/wA7c/nefXbX+ewPqR+0Wd32kOMRP7yG2tEj25x1nrOk598j3ouh//s/It1zGiCFk4p1Mv86Puf8cvrGXJ43P76HS7Oexjra5wfPqHf98lVamw9fJWne8fY2SqnFwFfeeMh/8t//4/pdhtEZo23vvUWnx6cc9CtM1uK6Ts5Fm+ukMm6SIOElj/mqCOhX1ywOkx5Nm0gBD7z+PpK82fZlyIQ5MwcsqRQXVlltz0hY69SqK7RmM1Zyi5iGAmziU0sJqwVNXrxMXJqU1/ME3b2afefAlCovUIuOWahqJDPlpHaMkIUcO/+bfzFb9Dbe0a+ZPDs2VOWVmzWH9gcPtvlvNVDNteZptcp3TiZkCmUsKwMTScLYcLHzyco0YD7hs137r2NG0sc9RKeXQQ4cULNqpC2mhTytS/Wcb0xXWeMZZSwFAdtPmBx6Qbb2SLDSEcRVZqHx2ws17kUrDtkAAAgAElEQVSXy5Gx5qAlhEGf1osprZOrvoVoKGhphw+/e8o3fuWrnO1/iLa2xWr+Lnqxxjvv/oAVaxHjzk32G+/Q63bISjkaxyeU7DxR/+r0/Ze+9hrJm/fRM2eElxolq8zf/wf/Gh80+9j+MQ/euEmrN2J7/R6TRgD6jMqLAer6bZ48PmLqXdeak8Al1meEXoTT75FRdhDFkFI+T7Rt4z9rUF+vsD+ds1nRCNtzwkigN50yPt5FT67KjH6oYUs+cT/m0PmIuGszagvofoWHN+rYfp63765zMDznD//gxySzIRlF5fD4JSv1LfKlq9p+3nUwhJj6ok0u6TLsD1koVKikI7SiTpLWODpp8NnBlFu/9ld4KFY5PHpKXpZoXE5g8VrF+kDaR98zaTsjOpkewb7Jy/dfcPcbOs7slFKgUajVuezucvDuJd///g/5TrTCr33VJ6hs8N98708AGLTPsAUBcxryq3eW0c2A8cCn9egzzEIWp3vJrbUSjy8/QNJldneP2Ly1gWcq1OtzjOhqWKjvSUyDPk9fFji4eMrTpz/i9r/8m5CbsZMROT3oMYhl5oJNNZjTaI8ZRU1+2RaRbQnd+jPAYux7CWSznJ4dgVGCaMy0c8JivkSrt4+cLSHNRlRyNnISsLlQ5/TpR2wXaqRpwsy7csNKdGo7N3lrXcM2i8xqML1wiWcRappQXthiZTGLHDss50aslHaY5hvsKDYH3TGHe9ey2N3eBbrioo7KJJ0hUWQQ9qYI0hIOEWneZ7/Ro+VvotgbbFQ8hMmAghlwfHryxTqR10WbJ0jeJUm5TLPTZblwn51XbrB70OXlJx8y7R6h+jp+1WajItFsNghTF1tLWPtchu0PPnzOguTyjdd3GE56vP7mV9heX+PouInmuJj9BMN3uVNdRtAL3NiRSeUV1iu3+PD953z4+TzGe997j7VXXqVgrBPUa7SHAR/8sMk3fu0beB2dWWeCNi8wOlVQ9DKylOIqp3SlMuaaSia4vhGZn48Ym0OK2zXOj86pFWqs1h9yPtxj29hhYOm8POvx9reWGaQn9I5GBFLIzbxMoCvs7l3JsL24OOKBbWEwI+3DL5VLpGaeqa5Tj0weVF7j0e/9hFbQo+bZrCzdp3H5nBvrJsIo5uzzDEzTRJJYYJTOsVZW6O6F6NVVfvD4J5i5FYK5RWllA8FP+PS9n1Cyarz9lQecn7xAtwscDTpf+Ja1LVR1hFowKdkS67+0yokvkj5qsVKq4/X7iN09fv//esJab51/4698k1tCiVw8573H736xztnZCZ1mm2BY4Kzb586rqyh4HFzs8crq2/SHbSa+xPef7rO6fYux6GKjorTPOdREFsyrwBtOTyhVbDonH7FeSanevc9K3SK/cofTk6cI5xP0VCQ3PICjlKW6y1cXt0g7Hdp7fR7ce/Bz9+CXIhAolo0vptTW63ipiBKGxNaY1tkJiZ+SjDLISUoxu4zijginA9YyBt3jE2Rvylr9ighiLiiokczR4YTz/nN+82t/idXVOrG8ybTfo75UR/Ym3PrWa2S8IY4Wc3/NYEm6g3EmIMZF/pR2QxENhLiP7TncUDVeffAK3/v+93E0A3tnm0xa5eGGzsv2iBcHBxQLAlFVIByolCvXmyUjzCGjk6ss4IxHiJklBoMW53vvc7E7wdLKbNw0KRYGDLsH9MsqF7NTJu0TtrIWinxV261VM6hdkdNnL5FufoVMcQ2pcp/RXgPJ8bldvokhB0QnLd7eXmNwfkESXiKoWxS1DI9Pr9LnxbKCyoDhNI9aMiByuWyNGfdOaF6KKH2R570GprfHRV8l0Vy2lqsk3QVWcgW6e0+/8E2OZFRPoygU0fMVdm7doXMZsXnzAZePd7E2wXFNLiZjRopH2YwwkRn3QtYqW3RaQ+BPECMJF5nlXJlvWDXy2i122xE7xSIXTxLCmzGVaJ1qtsLH3g/JJAGl2hxVFXj1zg5/dHFFOOoFZ2zXCySSTHc4ueJImHZQyytYgsHNlfuMSZAEETU5xo9bfLzfpGBVEbM2+8+uSUdnusdapkZJN7GqEB/MKa3IqGKZrKDgTk1KboN/fWWFgatQMGcsFg3iiUoucz2h6Scmr9x/m/bEpzBUGDZeMmsPWb1zm4HUo3h7g8sXx3zj7dewdAmnKDJyHAxLwu3PCOPPKebCM8JwkdubBUJR4zSJ6LSP+PjFHgvLywSjMjerHiv1mNPARhp5HD55h0VDZmWnwlr+5/MR/Hyy8/+PLJvJUynbWEKKKYng9WHUImeE5MSQSfeCJVtkSQ+w4xlq5OGOh8iqhaoohO5VR7wznlFb0Dltn+PPA447h5z1jvDiS0rVLCUrYGNVQ2VKrHj4YRNJSMh4MdNOj8nouqGiCAb5+jqpksHUdcpZhe2lVZJQZzYJ2Tts8ejRM3KySOq7dM+7mHGKFCcE4TVUdTaZs1xZoZ6tEcYGs9aANA7Rkggj9piHLUZOE8cLroAz1QKqYqFqIookMBxeNUJbR+fM51Mal33KpoLm+Eiexzfu3eL1rSUeVstsKBFup4NomuRLBnY+y6x/RNsZIWeu7rajyQBblRBEjVphk7kHyDaffXqIrlXpyAt0PZtM9RYuEoMRzGINX1W5GM3whOuzQ8pmQJTwAonZWUj7oM1Zs4+TpLhqCcWusbizzTwREMSAop5BESLEmYgkqASfA7gGgwnFfBW9UKFeX0cRY9q7j5n1+lhylVZzzOHzZzz64AOGvQbjZpuqajLtDJi7IaJ0hSOZ+EP0goxqZZDSDEmSYskWq/VFCvkikqoxbo8YTyHWymQXFrBkA1yYDyJm7k8pFI1l1lcqyOUyo1mFjCuiXTQpNTtERz3yXYeTH37M7PgItCGOO+N43KDpNhDM6/9o1BxysHtCu3FJJV8mdXxW6jVST+as2cdSDSazEb3xFFOXkWUVIg9PEtCzCvLnClVilFCoGtx58xVylRz+0Cdp9NDCGTnF4fYrJdxhl8PTI+LpkPl4imcoNMenhJFLyDVG4mfZlyIjCGOd+WTEPGkyHk2ZeyJKxqJg1AjGM1bNMq39Z4jTHDkpRvQilss27nDISllCla8gxpW1DI8PjnhtLYMQgDe9pNeZM7rc5+Hd+0x8GSnUeNoas//0A9bW7iJyybOzS8Lsa4SFa/TVdj3HpXTOdKhz684dZi24tXOD0XlMr9/CAOQgoXU8YyeTp9GPaB2PqBYWUaVrghMlVQgCmHQc1GIVo+9iWxI9b4Spz+hNZXJVk7XtKi/lKR8cniCiUsktYbpjspOr8eHAljm6mFAqrZCzlpl056yWY8bDMbXFIp6XUJSLnGoTFNelmCtwfNancd5kZuSYGVeDZwvrDxk6ET9q7fLyD3+fb7/2LfzpFfvPB7vPeOvX/xpnP2nh9IbIcZayLeAnWT768Y/5aqnIq1vXmPX3P7jkja/dw55L9MOE8aBN82xAy96itHKT1uElkuJyetQG7wUtMaRk23xlrc7x/pCjvauUPiPadBouW8VNUGq4nQMYD9n7pMuN5Ri/ecl63WQ+t3DPLun3XFw5y0p2lU5fwHeuNvDl6BmNyQJ5RcAZzUhUGy+UKaQGj87PqVTL6HoGzZSYtnqUiq/gB2Pmfoi1vYZdum6o3VzMcTYfkvgGt26uECYBC4nF48cDZlbIg0QjFycsLawyPi+g5MsMOqeoOQM5+1N8FJrEdDzAZYH0uM3kYsDdN76Csr1Bp3NAOgoomjWKYoaj5hRNz2JmRLZW6gTDJ5yfXJWrelYia0X87x+8w92dLSZCj/6oSLku8vJkn9fyKkVRxJtvctyccvvWOq29FvWbN2E+4+Vn3+Xuz9mDX4pAMHMSxuMuVs0mX66ghRJhquL5KXktz8baOi+fPGdFNSjrHr4mEM0DUmIGc42i+Xn3udvHKExpnY9J04hivs/6Wo1Y0Pjusx9QyBVA0BgFHoO0ycH3PyNxXRa+9U3aoy6Sfj2zXcgHFIsrdGYg9c4YBRKClcPWy8wnUxTNo6iLZCtbvDg9xzZCIjHHLJhQyF9fQ0qhgF7QaZ93cV2PWxuLzBWd2TQiKWZZDRX8+YRe9xDbjgARW3FZzNhMRy+I46u6tVCRsMxX6Z/usvvpM77yG3+RrbVNnuw+43D/kIksc/POJmu+jK7kmM1nyOqATP1Veo+ekq9cNeb8wQlb97Z56ks8vLnFK/e2cZ05aqHMG9Ui/U9+wsZiBc8zyekxr9xZwOk22FpfIhyNmHWHX/imhAbTEx95UiXQI6atkNtL27y6s8bpQYdbyyXEqcd6JY8YVHFbIbJQIIoyfPzd7+F5n4vXrqqslItM+ymWN4CLIXesCn0hZUUPuHVriTA6x3cNxHiF9mgPeZSyvrDM3lELdX512l0Mh7xsCmxXMqjlPKQTvLkPcpXFWpFUFOld9CmvZEkyKo32PuWsjZhkabQD+u1rIFhhyeb2g7cYjELsfouCYuIERUzL54ae48CYIV0sUvELGIUV9vov2FixsYKI8tZXgUcATJIUtbQOjsqs02Vn7QHhPOX4nY/IlwzC4Yz7y+ucvPyU08s+uU2V3iAgsWQ2MiKHyhXa9ZVVm/N4DJrM48Zn3K3JeJGHXsixZiRUklMiWySvDpEwGDTP2d7MkLEMkt1jbmxfU6z/LPtSBALkIpVyhnkYI8s6QuDjhDGaYCAlOr2DQzKkNPdOkSpZDN0g9CP8uYiYypy0ryLwxeCM5UKZtmmzbHmIRZFu7FMuFfnmG19jPHLwwoS1Qo2jxzHR6jpHB7v0fA8ru0lndI0RL67aqIsaVsdBnS0jz2IqeZsPn3aZjl22VlX6M4/762XM+hSbhHQuouZkWp1rWqhObw/xMos/csnbIcO9DrnFLdTZHEkvsPvskOpiFdPQiZIJlhbQvDwmMRXcwZh6IQeMCQOJ0mqFghrz2v015k7C/tk+khQzR+TSjek+uwC3yyuLGuF0ytFJB9la5/7mq/SFz8uVNGE2HPO1jTt0z5p0GkO6R+fISzJLlsG43WC1uM7T/gAja/L8+TFrhSpSHHPeHrGQuf6h1hZMvn73a8zFhEQSyRVM8tV1hj2VcJwwHfbJ5mxeW7zF3t6AbFakHc6JKbC8eQPX8eDgglzG4N7DB8wnIc6LIapSx05D8laGJx88YXZwjCQNCWyNna27tE8ekykpXOx2UfQCkXFFQ7+1Uaa4liFTXyQKHS7OLsgpGqNRQqGwRa99THUx5eFbW3R3nxKbeaa9NmHiMk8scqtFWu9f+Vap1wk5R7MUoonA7FxHKp9ytNfgx85HvP5L34JZQjl7VX5lhJT0tEXlzg3aL6+RhXnZQEgjUlEjra0yHY2ZRglGNsdEF2k+7lDPOpztnnBjawdrGlLM5FjNlei3XpDTrg65J41LOpMRVE3q5iIHhzPEvEw9ztIT5lycyziDkFGvzebOGv7M4+ODFt/5Sh0tbjMX/wzQmc8Ck2wmQzyfMxs5BDMBK2vjzRJUBUgMpERASUTcmUHgQaZYIyf5CKLMuH/Vff6Lf+lfpZadMG3tIigDQnmOnwgcNi6YlUvkzAwDfwL9AHXxLsP2lKU3yjQdHXFukvupYZHIEbC9EvPI5ol7ST1TpH/SJmMuMvP3yJSWOL9s8KN336e2UUWTCgzmE0wS6sr1a01GY9pHu5DoiH6KlVgsSxL24gLtnsedcpZg1Ga1uIiLT9hrsDh3YRpRVESC+ApZ+M2v/WUkdYZQLFDPaAyHbdzYQSkLGEWLgmjSCwWiiUVSLzKPLdRihsFgTuh5KPYSAH4U0Ot1COKIRM/j9Bw2Nh+wunSHSXufbG2ZYOSxmSbIA4dCvk61kGFyOkWTLHY/e/KFb+WlJZrjLquLyyws3uPW8iaFTJ3zmYzhKNzO1ricNhjoUzxrg+akj6qnnPdDtGyZ0LkqoQRXYPfjXcIoS+So3N15g/zxnNnUpqAE2ILOk8NTlus6J40mS8Y6nz09JLe8iDttIwyvspRcsUimaCMJU0K/x0pZRdcs3BlYWZ+ClsfOhHjdffK5Cogp49Sl3XcQkhxryyV2P/dtfHGBUa/S7/r4U418bkx5DDpFbpgag2cnqJpKezQmQmG5WmB8fkna94nG19fQ1iwiTKbkVZglCaNhE9POsrlSRMll+azZoNs/ZKmu0Ws8pRPFZKw87509xTYSJOkq24ndkLwtk4gqF/02tpSlrGvoSkR2FDAaN9CtLPNhE68RUs5tkdNt9KlFty0Sjee8+XP24C8Yin5hv7B/QeznMRR9KW4NfmG/sF/Y/7/2pSgN/s2/9wNGk0sWyhZB6BBOOhiai8QUWS6hmxJ+ICLgUKncZhaLzGMJPZMnDCyy2Rr/0W8s8G//zb/J9q0t3v3uj8hs1hGMLEY+T37pNv/8n/wjNhbqSDrkqjW6IxdNi4jnM0bdLje3S0S9mP/uv/ytq2f6j/8HdFNkfS1PXjHJ53ymvQazAIq1MqNOg2knxM6ESEqBIDUJNQ0vNtC1Cn/rr30TgP/tt36HWdAjiXII/w97b/qzS57ed31qr7uq7rr3/dn3s/U53X26e3qZ3fbYHmLHJFIQUhSQASGIYhSBsiGE5SQSCgmQF0EkEKxAwIE4ZiZC2B6b2dw93X2mu89+nnOefbv3fa26a+PF0/TjF5N5gXjRiFx/wE+1Xd/6/a7v9/pe6pyw12M2HKHFBBZWsjw52kONV3BHDpovIEs2VkomCiZUD3rosSR/+b/6K/x3/+kvkrArjIYDzqsDlpcrGHaBP7j3lO3NbdYWK3THMoPGDG/qIFtnyJJMPKNgRhKPn/wuv/5fP+E/+e//S/R4DFUUicvg+Qqe7xP5cWbziEwxy6RZI1uxaHYn6JqMqnr0m22UuEFKdPk3f/kvAPCr/6SJqqpU8gkev/9dlos2zdYRO5Uc9YMjHP8CTU6SL6YYBFl6Qxc5Y3FQj3h8cEG/7TD57X+Hv/uf/TniRhbfFRkMpxRyeTL5VR4cvCBfqXDwZI9cZQlCcIIQW/YoZi1awxGt81NE6Zy/9hvf5lu/91s06m1QRVrDMaXFLeaEhKMuMjKZvEW1PcaZC8TjBrLiM5uLqOEUXQdbDfiVr/9bALz1F/8qhq2zkCswng2Zu1MsM8Xw7Aw8h4XFJPP5BDQZy0qhpZK060P6c5iMh/z+r/8NAP763/xrGDGLw7Mx7TCg74/ZiSd4/9E9lheyBCoEOgSxEisG2OmQg5MJOcOkEAx47YsZfu4rf4u//ld/A0GKiMc0iokY8rzHlIjpsMnADZAkg/rFObpd4cZClucXTVKFMmI0ZtqF9z/a+wmZdxWfCyDIa3tsL+i0J0+wtBRSRqRzUefNW7f40eM9srEEjQsfTR1i7STwhkMSCHTbTzg+bSBrl62xpdUsh/v3cPwWBT+BIafREnFeNM4hGUdbySHJoJZWWCs5vLj/EKd1xFJmjX5jRCl1RY2tWiOk+AzGA1Zu3EGcxVjayLPbr1PrtElnlnC9Ie3hCcs3U1w8PcCKssjzMSeHzz9bp9FuMpucoBk2CbKE5RySnmM+O6AVqRiVdcLQYXTRY+X2OrNxSL/bI6bFmUQzKuZlA9Ni6cs8PT4jk7vNqlxFNAzixVXyOYt+kGCafoNa7zFW0WDcukCbZ0gZaSKxgCEnsY0h8IRUqoCia0RhyKRWRZ/PyOsG48mY64vbeOMJPU9B6VqITkSvPmCxZGOFKpoiIalX3YfbqS59f8qoNccWG5w9/phJr4UobzM5/IDjBz+kvP0Kzb04pWtvobkzFEzWBI8LvYER99gDFvKvcXK8j11YZjre56DVo+bqjOYu0aSLfWeH3eMLotmIzcUSjqOy3xSZDZIkIxUxlgS+DbLGaOZjmQXKKwt4qonvTpBsG13WGbsBXiCj6xLjdodQU4giE1+LMew7yH/MoSiXhVnzlPl8QMq06U5aOMMe6rRL1tCxh01C2yIQAqrPjzESBhoypjhkHF1ttM+OTlHiKeojjRftMRtvv8LTg31ubN1iv3ZGPFNESeuojoqJQ//cpX3SJbdk4xlLmMrl+58M6tzYKVFt7OIpi6RyFs2LDsNRwO6sQTlbYP3uHToXNSRLpLRoE4YNVETsrEo2dyVy+knxuQACW6phI3LaPiRX2WEu+CwsFXn36cckLIOt9VsMnHPm4wxnB8+oXTzBLG0QqCqiNMX7dMDF2O+CnaC0nGVydsyisc20GjENVcqrX+eTD3/M1uIycUkkGaV401zifBqwYMWpDzosWlePIxi1GI1abN16nf3955iaStgK+dZ77/Hln/kzXLSb9B0fzzeYP62iqRE/fr6PJEi021c0lDYdEEtm8CY+E79Dq9miV79gvVBgFDQZyCF5I8769SLNTo1wprBkW0iJAqlEkXb7kj5szzyWFjfpSVkGYki7f443P2PxxkvkSwt4ZkDM1jg4PeHxJ4fk0mm+vFOhN5S4/6OP+MKtd4B/QMyMmE6mKIGMaeZxxwPUQKASQcqZcfa0Rso0GIzGOP0+xbRFzFEYtlzc2RAjcQUEyuQx0UUdVU5hu22ur2QJigkOTw+pj0Os4hv0xARu28HdPaW0WmAezHC7PZazOgM9Yg+YksBK5GnPRAJZJYjPGGs9Nm8kOGj1merHiGaIlUzRnp7RH+SIxz06nsR5o8VbK5fmHRetFtmbLzFxXCINpMhFDuCi53BjfQEzlAj9Fro3x0umkNQYomHQ7nUw4xlmo/5n9xaTZxSzWXKyhtaZsKpk8VSJUUxDDUHoK8Q8kb2DQ3KZArInI1lTBDVECK+croxCiuzSbWKo2GOX7+4/w5KKaDEXaTHHVBjzZmmB/+N/+Wdsv3EXa+7xxtYajC2UkUTv5LIQmhMkotEExfXpO1PC8QiPGqgaa8UFtMo6PQKk+AKaHaD3PB4/G1ApZdAkmOpX9mk/KT4XQPBJu8FN20BMyDT7e+Q2tpAo0H/3hPSqxcnTY6LqiEK2QHFpkY2iwsjx6CsRydgyw0+5bTMuc9YaYgsjum6fmD+GYUhFSOCoPlp6h5iZIWUt4B29QO11mLTO+ejYYfPVRc6bV12DrV6bpbs3mJg2WjLGUBAYDefkrr/N6cgnFItctBu0p6fcWSxihR4vrZV4cNplJ2fx3f97IWeMJHnM/CmjqcryZoF6S+BASKCFIY1Og0ZCxYyn6bXOKcVV/FkHe+7x7P4JpeUVANSJwUl7wDTtc9aZcDbXOT054OXIxZ59zOpWhr7u09DrDApjjEqF59UqgZ9BL97kycETAAQU7LhMOJOJpl1mozmRKtLrjlh0G1gDj4kvUD3eRctmUJI6s7lLdnmNwJojGVd/u+fHB9iqjSw6aKJOpzPBThmoehFiKUJmdPeaxNweKVGGZEQqE0dPS8w7NQQuVXOhZPKjR7vsfOMbBAMRMdXB1Zs8o0vqNZH+3jELr1XoT+sM6wHl9VWkVkgiU6A2d2iOLq9pMpcYNVpk9BCnNSMQFGaoFCyL4fkRTjBjPPaJzAT5pQKuEKCKcUIrS/P0nMi7mobtOH3WYouER/uk5BJaL2CiSWzGFwnmFqoa8p33fkTCUSh0e1yYPnLZoBtOEVNX7NOJb7F/WiNrSVTbEmZ+kRc1j6wgkRofU5uN6adW2bj+C5zoQ2IJhV96+xvMLqa8+8N3KSQud6mz3iHZpS0uNIOO4xBpLk4mjbK9zfOxSuBHLMVN5sGU/fEzdFVAt3sIskDME8jlr9y3flJ8LoCgmM0ipkwmew2GvkX3uMd6Po4p9HjnpW8w8CJ2X9yjLzt0Hk4Q5Rn1i13K23kqSpbm+WWH3v7pGb6a4HC/Rjab4+OPH5OIrZFaWEDNpph4PW7KKsOjY5qH+wzDNnPBxsjJDIMZpnIlMbVLBZ6eXZAiTnIhjT8KcGMawVyDSYr+dMI4MEhlv8RZd0ioQTIZcMPQGTeumlcy8SSCBv1hA1vP0JxrsHWLYbzILFUgTPfphwIpoc/5QEHVTRLTCHd0zEZaR9Euk8WMm0T9NhuFBUJVQUj6zM9duvoD5BiMxCTFV16jqoekF7M023VevfkSow+rxHMx9E95ZEux6XW7uFORjJJneydBbuzSaJwyq87pP95HsNIslhcxd5ZJLCYZmB61QOBi2MDwr/4sxbjM3qMnfPHmTSJxjBJa6GORSiSQNcqsr1Y4Mx4SWbdQXJdZOCRVMXn08AnjaocJl0YwgaWz8+oqC4UYD0ZNPG9IdiPgbPaM5nCf7PUchXwGaQiCCbX2EZvlVcLaIfkFFXd8qZEIPR9bFiiXdjge7aPYGsEkRFY1DEMjqVn41T6T8ZDOUMJzDabRIeOpimiYeOEV7Sf4Os92n1GWNZyTQ4q9FIuJGNmMihGL4Qc6P6tn2Dt6guwqCDOR5N271AZ7OMEVoPRaF7zx8its7bzGf/GPfxuvpfD6y18mLgis3v4CzffepZrI0J2E6H0RUZrR6Ha5uKhhrmc5Ey5BTkg4mGtllOoL8ukKj48+5rlbQB33aY7jDIcOxZxHOiZw3J+zmE8w7MKKEZIRRywYV7L3nxSfC9YgqUuAi724THlpHVO36U+mjMwMD9tNmrKMvpJjKApYaZvRbEBflRjNHAajAbWLBgB2LKCSUdgopFnKxXG6Xca1C2xMtmMFXi5d42amhDBxCUZtxv0xkaWTyicQxQl99+oFdkYDpnOf+kmbwbmD15ghzXIs2svkEzcRR0lKsRKqazNqzGn1REbTGIaqI8hXbKg7Cmj2B3hTmeLKdVa3b5LOF5ETRTxRxzdSZDe2yGcKbCwvUynkKadzyGoM2xSx9UvZ8zyISKZLZIoJ5rMG2ZyInPTJlJOUtwpYqRlp2yWZCxFUh5XrJc5rp5jxkEJeQ4gu/1Ij18ONBBRVJTJMGpMhqq2hpnJEskin2+XgxSNCU0O2NWJpm3yhTKDGUMQQd3jVhlyxkqSViJLoErZOsadtln20VhQAACAASURBVOMS/sxBnI0opzKk7BRpO81Ly+usFyw6rQGiq+JFMBp+ajrb8VBiRUbjBiItNNOlMahj50SSCwJSwuVp5wGnw1N8YY6ahMPaGd3hAF2OkORLVmw0dxnPfR6fXTARFLxuj6QcEvdd9LnEZFgnKblooYM2ddCTcSw5hqq4RMIIIbgagpsqFElkS5TLW8ipDLWjY8adKYosYoYQTOe4QwfHj5A0ndXb2+jZFJqp8ccpecsTKdghH95/gSvrzIbHBK0T/HBCQhQopmXC+gGjURU9ppAtlBj0XTTLYdAdgn5Zt0jaFvNZSNYoU2v5pOxtPHmJiZujXpMY1OOcNE1aoxSTSZHjuoaZ2MbzUohhDCP86Qz95wIImo+e4HY9JgOFcnmNTDLFxWEVrbLIw7rD8xfPKORM3PMetUaNySxke6VCRrQo+BB1Ls/khcUksfiEw4t72BUZR3JA6mH2+wTnbaKTLmbiBmKUYapodDsnZErLOLJHRIdi5opmlXpdZhOFbTVHsSlQHMb5plLg+kgjvFdj4WLK5kTh2lTll+58mdfXXudabI2MLBMLrs6a2lIBwciwkV/h8XsfsSTbGEaAg0xxc4OF669izRxWVm/wzptf5U6hwLLscqNUZgYUly5dg1OZJeJWCU23qSLyu9//J+Q3Jiykq6yV5+TtPgeffIvxqMcrby8gGAlO2idsvXSNha1X2Xz9GwA8+fB9Bt0arV4fPy5x6513SN64wcL6JvVZnYcv/pCeX6MxOEcwXWLxiHzWxBQ1CvEYsT8Glu29QwxBRZr0mN5/ROfDd/Ef7LEjeixNRSaHz5GaDY7ffYzb6iFOI5YlixvFGGr/lNq93718b+kyp8/aKOGUYlEilaySyI6Zu8/JqC0MZYAkBahzn7Ubi0RihGAnmagarchAXbh8Rm3Z4KgxRg8DyrpONmtTMA0Ed0Lz6AmJ8RDD7VGQfYJ6A1EJqdWfIsdMQlGlx9WOQImJLN64jv3yEgNN5/HY5fFBh2Z3Tms2x08nGCoGUVrhrF5Fs3IkzQxff+cNlkpXdZS7X/8idiwiGW9xqxKR38hx57U410yNrUTEn7txjV++u0K+/RjTapONzzl98R1GnQaB08FP3AIgqXg8+OD7fPe7e3T2ZQb9FebNJAxK3Nr4WTJbP4+k3EZRN5CNNwm8HQbjCgeHAvXqmESs8VNz8HNxNLj/ycd8o3QDxc/hT0yKoYlf2iFpKEyf7rN2q4AYzKl8ZZ32RZ8RIfbeMaGqsVAocjMt8x2gYLh0DZWtr60xEWr460vUqxLH7/4Wf/Ibv4LswT/7X58w9WqcCh2Uu2vs+h+TDHos3SwhhVdHA18RKYrrGEKRTa/I/vmE44NnHH7wkKy5QGlBZTp0aPROES+y6OaEZtBF1qbYZvmzdczMbfr1B/QHdfzJmO9/9w8wX/kaNkscn08IT++zqY/Yf3zIjbUsf/QH+ywzYz4ekCguEEiXfQvtTodUvszvf/yYQA+xtneouQ2+/NUbJFWJH/zT32F44FI397F3/iLVI5+XKzcxFIVR/4La3qWKLzkaE09A+fYOjVmHF40Yy6+8zP5HH9EUGpTeyjMOdWZGn+TmAlgmzckc3x8wGLQQuKo+6/KA7WQWZ2Sij226tSmn41PSyTi5cZXGiwldb04qZfLsgxYbb8XpTtJs36qg3twkFxzx93//hNOLI2aoPKqHWKUpipJi4A2I22Ua9S62LJD2bc67cCb6iE2RzFzDE0LsWILR3jEA8fQ6KWGG5AxR1Ajd8Em7NYrZFD9oR/QdCVVI0XJ8khkbQzYpbd3FFYBAph1epYM6nxEkIiRbZ4TE0t11Pvnee1QcG3PzZeJLc55/ckRnckxUMthYniHnZDqBx9bO1mfrjCZzfMvGdJ+zvV6i9eCI3kf3Wdz6JoFrsGCXEacON1//k3zy+Lsce0dIowkF6xBFndKb/usAZCo+731cpzZKoR6dE93cYOIleVZ12JJVnJHNxf4BmcoCjV6fpdIm0dRFT67R8LoIex/91Bz8XADB5PCElxIZZtY2e/U6C3OfoNvnixt3qJ6dkFUSjE9q2MUsOztrxAKPZ/e/S2Vng/T4DNe93BEsrGsc1Gvc+dkFjp+ds/lOwKwtM37f58P3f5dXd3IoaRmnXsdYUJE2ElwrFsiRIEq1EXpX1f68WSBW3ObFmcF5fUhBUaj1e8QjmYI2RXIdjmsH+L5LOWtzuLdLTZCZmyr5wpXl94//6GNC0yVwJXw0Hj53WEq1+f6H38Evlug32zi5BAtSlwdtlUHD5dzx6NVG3LLSrKQuQeV07CD5L3DUgLW33iYaVlHTx3zvh4/YqpjcXv0yQuKYP3w+5v3/fY9s5TpvvbzBxaNDtou3+OGLy8GsdkFnY6WEOx7g+jb5pSRPz8+YxiSmlomWyTOaneOqQ+7tPSVfXEAxEyRyFpaxwmH7g8/urSRF5CoV/vm3nrNVXMLtv0/TCfnmy79IZ/c+0hx6eye8/caX0NIJgpSIIuiM+l2cSQdTvTy3zqUMt19N0A3P8Q2Z8+OnJFfT9H2Bu+tfQp6KLC6s82yvxfGRizYtg6Oiaz5K0KPVu5Th6ul1+vv3KMYU0qLHim3z6MNTMks5Vhfuosxdhr0JY6eFMQuJ97owdhnjMRFlQm3xs3tLJQUIPA6eH3Ln7UUehVXyW9DxjxkKcUbdDqP5M6xVG0oGneEEo9sl0oec1B9+ts53/3CX2prDontIOb3Hm94KGze/yNP3XvDlf+/fZn6xT3B6wd69+2R0gWLc5lmvfzkQWMry9N1LHwnBCShvvA7cRe4rtGJZit05egSbrknKCnn1zkvI3pTVpQ0eHD7C0JZI6ybvf/CUX3n72k/Nwc8FEPyZX3yDsC1zcl5lOA4ZGBKx/QYXnR+hWwnctkWnOSWlukw7DfZ3HxNbXUSLirheg3Rw2eQzHo6ImVOaoo+ryrxwzxgliqx+dZWTd58zm1XZf9jgotNgc2mT7eQOllQkwGVw0EL5Y5bPd7Z3eP9pjScfDVgVZe7cepNB/RzdMPEMMEydrYUSbjhhIePw+PmAH+23uPalbb5xe5u/8ek6nmAy6fYZDeaEiwVCKcnFeY/l4iaPu1VuXLvN9LSJfc1GnUNonuM7BlbB5PhFjfPVy634J0+PeflOhXJpkaOpgjQJeXL0jFc3ddzuEOmiAWi89NLXePFbn7Cx+QbV4wnDfo2+aHBt4TJZJpHKyHGQkwG2ElE/rmHJMkLkMRuO2Lx1E//xDB8Vp9HHkS0MyaTWaGDaHnlb/ewZbRahVeuREFPIQYvVhR3c/oCDF88JZgL9eIlm0OMH9x4Sv1agHK4SpXVkMcNbtzbwhIdAg8bFKfFYxEYpzbk35JXSBg93v8/Lr28jfnSfjFVhenrBknWd/fuPQE+yO5zy8vUlxtU2+dSl1+AoECFy0RIGsqHz4qRKcnGFSbeLa9tMPZfCQgosg0DrI+sa0qB9qeH3ZJrCVRu6GcyYR11izpTxxOE0GrB99zqtWYfT5BzJHBGUEzxv1ijHlumNm2iNU4aKAOHVEdN0FVpnA3qCyjCSOB/4qP0WVSHio9/5Hq+m4zx+8ISvXvsKQqKLo0go8Yjlgsr/9DvvknAurXKeP3uIat1FOD9BiW9gT6csrGyALILeQumF2AmLxuET5nGZb5RWOGteMDytMWh2OO39f2AsOvMRH370AfdPXTZXt+nmV5FlnfefNtnZyHL/3n1ShswT3WQ0GuOzyPIkxrv//Pv83CsJxOiyyJPqHyEP2gRDCII5O29t0JFz5PUigdHDXhaYHKgs1gzyy0uUlteQu0PKmQUMr41qF4FLB57z0wtm8i1efS3OS3Ebv96iuCYzugiJFJVnrSPCWJLpaEp7XKIeUylsmsQlF7Vy9WcJUnNKhS2E+jGppSyDscBxr4OZ1Jhf9Jj3GwRalaNainBY5avX73BytEshk2U+1vCEy3Pr1vYqHecMrdmjObGJnCmZQZKj0xbj2hGhBilRxi1f8M0v/TKzkyF19wELCzHc4R5W/NK8Qxc8Jr0B66kc83mbwNfo+gFKpJEqLTBiRGL7DeJLd+noAsl8itrxPpImMTg9w1KvgODeey9Q42kSik8gZBGzCqmVPA1d5KU3vsL44JhRQ4NCnmF5DaGcgrHO7OiY3JZB5lNx0vZ6hnZnF1ObofkO0/GMW8ZdVt08TlVh0u8jqxEXXhNJXGGxUCJ0XtDunpKXk6Rzl8+oMxW4tr6OLQ+Zhg79+RhJsxgGIgybuKJOY+CiiWMUZ4rv9FlcyjJLWwiDkO+/e9VQFZ/CbDSh3xzjZ3TkQp6zwZg7X7qL9NIqRlrDMGUW6lUUI83B/oBx6wWNKM6tL1yZoE7dHrdvbmMVKmzdeYmdTgIn+Sa/9IbK5AcHnE49/EQZ+0aSgqISy+co/vJt/sH//A9Z3LpBtX9Zb/KMHKdzj1d+8U/QPezRbbYpWSHDSURrdw9j6KKqEot2hpc2vooZNVFHXZqGxPJGCUv6F7YZAJ8TINjMVagpHsd6nJohst9ucXtjmccNkQdHQ2r1AavxFMsZB3/ksX98zG7SQug3seIOL9+6A3/4A3QlYDTwUH2Ze0+f88qfWqN/0SNbzvPON29wOt1HaQ7YWCzz4sk+w6c1Xk7eoujpGJKL4l8Vwm7e3CKsDfHUNO3+mFwlpNE7Q3/rJo8fHSCjU8jpOLrPafcZRk6nFC2xVDGopK+MItPGjJHvs7axTL13RiydoZy36bomX/2ZLdrNLpMXTbbSOo8PQ6bXIt558wt4ozHToYlhXfK/YiAxFkz86Ry7c0J5PYeUvEn/fA+nn+T46fe434n45p/+FRILr9GpP2exXKF/souhZjkZXe4IvEQc19Ro+yKelmM6DImLCrJkkFrb5KJ5ghlfwM+UyGkBohSwub7EeDZm7E0xEldTfAw7Tc/xCAoVOtMx22vL+PM+Z6JCw5kipMq0Mk8YWwY3jQSdTsR4MqCgh1jxOMXsEnAPd1ijXm2xtlnA6/ZZu3ENMQg5flpj/sJiPBbwhBj9uUNsaZX9j55y861bPLl4gRQrMZ5eHjEaM5+3V8vUDmuowpRyvkA0G5PMpbHtBGlbY9Tps1efYORUAisg8icEHZVeP2KmX7XqdrpTvKHMrCvg+iMYgubHCJICQtzFShWIVA9V13D6Q2RfoNEeky1ZhP0r+vj1b9ziC7e3OTuucvDJjGS6wMOnP6ImhKxMO5QXk2QT65wf7pO4s8REHPC937+H1xU57cc4PD8G4O61W7ReQL32hMrNbU5+dMBGWsXMJlndusOk18TI5EiPmhw+/TYXk5B6rwHZPEZMJJW7AqefFJ8LIEgVM0wljRvry+w25qj5kHPFZeWNVWQ9x13xJkrgUaufU9zOU3wtw/d/7//kF75ym7h6hPYpNeZGMrYjIRsyhmVjWBkylk+pMqW1X6U77jIYDAl0hZduL3Pvk32edw/Rhm1KhsJyugS8C1weM2ZRG8uY0hm5hIsrGOJNxrUu2Z08R60aWlqmow5ZKBUY9Tq8uVrAiMNAvarQfvyoSpQL+UR4xJ2dNeTAR3UdDN+l7enk9CRRwsJLpPmFL34FlQ7BeET15JxMMo8RXX6cs0nIzbt3Oev8mIxkoTsSmp2hMdmjdTpmObvOnXKaVzYW2N07Z1qbc9Y4J5NfRA1NdPXShjwuyVhiHGEgEAUtfNUks5ildz5El1PM+ucEkUAQOEjihN5ZC9OKEzkhyZTEZHRFsdmaxv54gGin6U36hD2XRDnF7S+/wWlrhBHJbHpfotp0GFViyE6IKE2o9nocn/fgU0nC2WkbPRnn4xfPWUiXGY4CwgAcP8Az4vjDNkurFbZNg56goSx/gRkO6ViJbm2K+OnMwt3DJ3wcS/KSUSAIhtS8CdJYRQ59XFvk+VmNjGUz0mMMWk0MVknYOuczCWNxmZR0JbrptfsoozS6muSsVWPidlBSNqIPux8eMd/0GfZAR8X3ZVqDNteXF2kc77GyvPTZOo8ef4Ipueysv0JtdMzp6TN2Hx3QVeKsf/PnuX9wQqwyoDNsM56tokoxYn6WzqCKJWdI5lO0gMLq20gHT/jxJ9/m+V6aVn2ELd+i0ZySjufYvL7I9z/8EeG0Sb8b4dRrLC6XOD99yFvXdbLFq3kUPyk+F0CwtLnDjy/ehyjOoFZHyqaJyBDqeSQsUnZANB2haQ38cYfJ3Ocrry3h9musXs/jDy4r4s5eG7EvI5kGf/brL+MYPuospPb0gNjQIWrOiFoCdcWndv8hplFhfXORaWvI00eH9C+uPPuNpMyz9z4hYSmMxCxNZ8TG8hr97jmSGcOuBMQKEm/fXiNvz4krm7x374cIiRJm+mp01rU7RY5ap7iuhCpr5EpJ5jWfUjaNLsexI5lb2W2S6Tg3MmlOPjnFMEW2dpZotoY827tsFlHMJpadpezHiZtlnFaLbiMgI21TvLmBe7hLwrLot4ZY8QU0r8ZGcZHTdoPDkwPW7UtAMQ0NW7dwuj4JXSGpRFiDgP3dI9RsgYX4Jqfn+wTmjHg6iabLJIwstV6DomUw755+dm9rm+vsx8b48Yja+QxHTnBxVqf2gw/xZINwPCaMVEwzQPZEQiVGo/6QxRRIxSIql4xIrCATxoZ4skBPbDI9rhGPp3DFCDNhkMzkEdwhMwScIGQ+HZHPxqjXXAbRiNfXdgCoz6b0hRXmhkIuvsTJ0X0yaQ3FjTgZtpjjcNx2iekSop7jtH5Owitib9+lJViE2tWkq1K8xNCzuXF9ndajkIRRxHG7DKsOi4tl/JaK3NMIZY2gD+sbabKmQGJewJSuaMh5KkvDnTO4/wHHozrNp0+489rX6Yzj/PDBLtczGu3qCfdePMFMiJwcnvGlV67z+ls3+c3vPsQbXapmnYHJdODSdDz0gkZ5O8/Y0shlcjx7eES/JnPsTAhnAqVMRDKb4bxWpeN3mMivEC9cDW/5SfG5AILVzCpp44Kh5/Gv/uwrhPEEG8srfPjgiExBozceIA59euMRWyurWJbG3uPHKLqAEE159fZd4Fvs7h1BlMNOe4xOFPQwYqeY49sP+pSsNGq0TEFRmZ6Meevm19jfryEPVKaTENmdYctXVmXexGE7WyK/muNsNmU6GzA4fA9ZyrJSTuEoMtK8j+vIlLaWONvbp1KJIysKw86V9113IFLJlvGqZ6hCjHanx2AqYyV1qs+fI2eSpCsauhRn99kuiXSBmCDRHbt0hy7P9vYBWM4OiPkN3n7nFT75wz9gduHRax0R12Wa51OWlxewDZ/l9Vt8sPuMxWIcv3GGLkGganx8eEkfzattHNNBFYtE0wlZTUadzFjPJBmOehQKS1jCKs9PL8jnK7jjAUqrBYKELEQk7aujQavrUttvYC2lWV9YoioJ2KUUe9UapXKJDx58RMrKkyQicj1CQcQQXYQwIhmXkeeX7jtK3KETzUgVDWb1HmFoYowmhPMuvqowESKIPPK5LAldwhm3mDgRphEw8xROmk8BsLI6YT5OTVZphlNqgYejx7BtDUXP0+/XETMx8gtFOhctAqtIK/DoTQOGks9EuGJ7FMHAG3U5OU1gBjKxeJbDqYIZCUiOzaPnAzQvjiGGZBaShFFEfzLFkA1U8Uqec+/FLjNphbjnMpidoZV8vnh9EaIlmm2IOrvki3l+7Z1/jcbRc4yby3ScM+TCMj//pbf48ON7HAPPah6VQoVas82drTcYzeZUW1UaPQc7bzIbNlDFGZLiEYsl2Fl7ifXNPjMcllM5jg4mfOmn5ODnAgjGgy5rWQOtqGMX4jw9O0HojPmZ21nm8wlhSoBQ5lQvkIn7THunvLyqwXCKqioctesALF0v0DmL0PwQpjZ0QnzHozSLEfdDUkqb+bjD3A2wh3O+XCwzbl9QUh2CZEjcuvojnJ73MLMZBiEUTB1B9ZEDkURaZ+w1qRgpNMtCsC3OTk85PDjAiqkYesAfHV3RkGIujST7rG0kaPZcZFHEKhbYLuaQvBB8D4ZwdviCcjmHKis06i0s3cSZzhBnl4qw+48uKA8TtE7v06oOCeYWpiuiUyQfd0mJOSK3yXd+90POOlW+9oUv0JtNsHN57ixOOBcut/Rev03oO4jM0WI2w7mI6HlEsxkZzSY27HJ88IJMXGRaPSWeTBDOfDKqjDseEjevts9Hp/vcWk7TDLo0egOkGISyScUUOH72PSS3TS4RoJpZhpMz5tUGN9dSJFWB8xfHxLTLwmMln0ILDMaDgPrYJ1AiBnOXZJRlOA5IllRaA41udUDf7VPMxJCcOalkmawypqBefsbltU2CVIL2fMh82sfMKAxlkcNul42dAmosQpN1us6cMF5gPHYINAvX0xiM53jKVY1ADNqsrShUu2dMuw3UmIsw7zHoa5iWTHJex3Mm5NNJTs72mXYhnbbAbxO4V3Zum7cut/tq0Of2UpnVrQpmVmJc75K0LN6++zoffvQJ4kykWEzBoM6Lszq9D+s8OZyTN91Pn3UXK7PEzTcXKCaXMOQWW9c28AOXbrXJea1BNrGAgYoSN7BTadL2Cs1mDX8a0Lio/9Qc/FwAgaSKSJpIXISiLnOCi9utslOpgOri+R4RIcXtBfCnTGULVTcZV3t0xlNGvUsEzmcsBF9lHoEiQyZhMgp8Jv0akq6iKCqJRBJvGDBzpyjSHGc+JWkKuN6M/uxKUFRrNokXdeadLqpl4U26xGSB1JqO0O4yH58zRKWQWmPuDtB1lVCL0WxNGLau5Jzdpw1mlsRMD5gO+oQIZEYBQ01hetYhnlQZNj0OT49oVM8QPIHD6gHFzBKTjk+neXnsuffREanqhM1rOzRrZ6SjBIc//oRK8RaJdIphp0NnUmOEzziUiD8+wMPDefaUr33xNaonlw1V+UKewAtwRkNkSSWZLTAbRDSHEzQtYhKGTIOQgmARMEcIpsTjKUzDRPD7ZFNXrMFy3kC0DVYsi0xWYRiOSKZtlLjNellH8BYJ3QlL69c5v+jipUVWimmmrRahyGdNR43ajFCPGM5VhiMN2RCpdntMFEiaFmE3xIgX6c9CQjnHXJDJJ+L0qufcWl1kUr0crz5DwHEDLvpd3GEHr31BwkygIbB/eogYOCiCjOOHEBn4KPQHTVw5BWqauXn1J18sxWldDMjnLBwhSSwR0nd8XNelP1YplQqMB03SKYtxf4gZCcQ0j067SXnpatf01t2vgOqz97GHV4oDBpJk0m4eE1dSRI7InWslvJnHKCYSDgVOZI9iJkMwDqmNL/UfDz/eJbe0RMzSmEUak1kX3ZSJkLm+vYrnu8xGEs1Gh5Rp0egMqJ81CIOAxnkPaf7TRcT/0qrsX8a/jP+fxE+zKvtc7Aj+/J/991nbXMITZHxVI5wG5NfK3PvgY+JpE8NIMnBFZl5AJnKQgxBXi5GVRc6rz4mNq/zn//i3+ZWv7/Dm628x6Xcw02mazQtEYY4oZzh89oy7r71JZi2GOmzRd6ecj138uUhnFHB9s0S/0eBv/p3fA+DX7vwJ7rx6ByOdJ5bWsdNJ0kaO3acPGEUqK4smcXzakyHZSoVJp0dctmkO+hw+3+PP/+bfBuA3/v4zhGCCgI8rgCX6BP6QYOLge10SmQIxS0MIRLrdJq32iNRyCcdxSMQXuX77C/wrLwv8qb/yF3AnLiJzOs1DbmzeIK7qCFqKXC5Nv31Bt9knjGQEMWI4dGiO2liRSHsCom3yR//DP+J/+8v/I88PzhD8M1pzDU3vMmo1UBWXCTaptM3UExA0k4O9CwQ1jmmlKNgBwsChtHib//A3/wMAnN73+eTFGePjU2Qjw0F9jqCAPxNYWk0iTCUudo8JohGiIlA0VXRNRJRyqEmbeuOMP/3v/iV+/b/5JVbXruG0h+y2+ySsJY46fVzHZ3t7nUHvlOX1awz7I95/8IjZdMor1xaZdKf4QodKSubXf/V3+DlV4eXt6+hWHqOU5eU3lknY25yedHmxt4/nz5HmLURVwg9k/D4YaQsikdOz5zSrdX67eVmT+Y/+0i+iRRa7Dx5zbWcbnTy12Yx8Po3jTpmcBKiyQ96SGQ7r7CyVUWIpjtt95vqQ//hv/1MA/o1f+3voYcB4NIasTbc9YmmrjDP3CSYhomlhKhP6jke3dYYkKsQUk0D2yRgGBhZ/9zd+lb/1j/4hB89PkB2ZauOQsZoiEzOR40l653VOal1yhow7rpMwVOR4Fm0yhEjBWlvi4/0nPzUHPxdAIMe3mLYDDN0mlFV2G1MWrm2xtDhnPhdQhCSzeRM3UEklXYbTEfORzChp0OsKJFLLAHzhxi2y0ZxA0mic7qEJOkLoYRbmbC0qpDSHdCQxyOqE04BhdcatSg5ZGDMatTG1K2VZLp/FkIscvmiS2FrEHRyTy3ZpeC1iSpan9R6pdJy6r2KdB1xbvc3pw0cc1C5AvjojxoQj0lmN8WCE7HrMZgPO9p6Rzi4gCjOSTpPBPMts1MLIZ9C9AD8YE4Rzznq79H98qZp0nCpLyysYMVguJ9ncWMeZdRn0u8iCSi4bJx3TmIyndFotUvk0mQWDwcQnpaq0Pu0ajNk9rm+C4+ZJZ/IkCirPnx8TOCdsF4uYcZmxAf1+AikOC7k0c19E9SUMUcSPXbWzfud7+0zR0MQlWqfnHB61aFXbVDZu0OuHZEQLd24xixQyiolo+QTSHG8wxsrEQb7cQtvJFXrVEZMgS38w5fzgkFSlyLOTDolCB9Na4HufPGU67bCcrhBmbNByHDaOWMlnED5t+/3a13+GO6UvM1YjurM+ydLLzCQdcUNACOpU91rUxzK6JvGVL36RvJbi9p1Nvv3ffou4GdCwAvgUCAT9OrHsCteUdSpxk8bZiKXyS5yfvkCJ28ipAoI3xliMo7Q2SK5X6Fzs058pGH9sqjbtY1RLJlnO0Z2MQPZpTi4oFJeYijxBzQAAIABJREFU+OeMag8wlhZILNqM5xbNepXVxJy4muDg+Cle77K2M+oE9EcSbnOAqpqsxwV69SrjYRN5HHFnJUcqe4NyQeJw74BBa8DU9wmUCRe7j5E+FZT9C3Pw/1Hm/r8cirmILzt4ikynPaHvhDz6+ITRIETLWMx7PRrnbW5f38ZtVYmpIqlyAidIoWY2KG9tAX+H7OYCpiSSq7sk3CyqGJFNy+wHHubGOu/sbCGnCtQY8WKvyTe/YSEMesxnh4Rah0Qy/dk1ebLA7rBNIb9JPldmNaPwwxf3kH2F9bJFdyCgm8s4vT7xSp5mt4tRvkFWUi7Zi08jOPsho3EMwzKJJ9OcXLQQFI/iQordQxclyFJvtklbKjHdRo7a5JMxxrOAjCQRi19qJIKphzMcwFjGTmQIPY/WxQAVCOIB6UKFcauH5EZkKwt0w5CuK3DYarK+nKTevrwmy06SXMpw3hujJTKMI5ncWoTTk2Epj1nKE/Mi5r09Xr2zRSqnI00SvLy8Rncy43R8NcUp8G2OLgbEYz5iJs5CJEM4wYylKdgbTFvn4Ps4kkq9Dj3HIWZOWF/Z4PlJm7F8KXuNmcs8eHSP1OIWo/4zJGHG/af72GWVJ/ufkF7MMA9t8okKoiHTa7j0nQbblVUGzTbJ1UslZ9fZoKH7GIkF0vE83ZHKejzP4+qPEXyJlet5sh2LiZTEiC3j+SIPHjbRMxtoUUBJkuDwciZBIGQYTTR6QwlLcRkOhjyuPqSMSNgd0fAa5C2J0xMLM2Zw7/4D9ITN/shlJX71HWVXY6yWVnCCBDcMCVWJ4ZQKPHjygsPnD9gp5XFnOl5zykoxwXYlRdSoEzMUYss5BrE2fwRMJgMuzhvkEzFK5TzLpoArz2h3OmQKaYrlJENmTM9OKCUUMqkcZ0ce7x+ek8sYTAZXYrmfFJ8LIIgLBjPRwkyobFVU6h/v0kUku1SmXLIZTEzmmkG9NcSZzJlN5xRaPoI2IJyFhPYl7eflKzw5OOVatoTmBIzOu+yftYjduMH65hJ7XZGvvX2Xgw/28N0244cX5LJ5zKlAKV/B5apY+Hs1gQ00hoGDet6gM5Xx+y5BTOGD3VOE2Ih5r87FLKQ9qFOSdPTkOqPmhM74ap2R4iL4c6bjEfHQwbBMyptrPD+tohhJzuojElqMxmmXZuMRL20laVefki0vsn/wiGTuEsljU5c1RcfOlXm4d4EWxkgbOkaqQHswI7eq0H7RR5cU7GKWqT9CrXVZ2aoQkzyymct1tlYXGblNDE8gaUm88toaD57InAsSne6ckS1Q63f4v9h7r19ZsuzM7xc2IyPS+8yTx5t7rr+3fLVnk81ma4aiNAMSEDEvAgQIAgToSSNImBdBQz1oJEJvMwJmRtAIwmCooQFE05bs6qrqcrduXX/u8S7zpPcmfIQeTqlOPzT6uQhx/wEbsSNif3vt9X3rW+V0joWVRczxiHguz8moR1TUWUpfnSwb5RVQTT55+TGSY1BUDYrVFazjT3n2Nx9SLJdw1Rlyuczm9Ws4mketNWDizTAdD0W6rGTcPx6yc27h1R+gRwQWVpJsbujYaptcushodkIumkOTDQQhiioGSILKKAyIFhWSmU0ATCXJg8MJ6VUJTTNYtnxqJx/Q7B0TJsuMnIBx0MYb2zQqOywmyvgzganjoAUhU++K/08JCd795ADFaRBOI5hnzyjlFJajJTwF9P4Y2fPQ07dQYjqWX6DpC8TjY5TolbJUz5YYWh7VuEUhm8SUotTHY3qtPpNhkmPfZeumz0YmTSGlo4kOmbU3+PSDF9xaX+bx9JLJMkc9QtlnXO8wHHdIRn1ul9JUdRBrh8T9McVYBlOeQ+4Og8AgLFncydzFVxLYR4e/cg9+KfwIKoVtREnm4qRJd+Cxdf026kKZY9vkfNLCNEbc2tgkvb5K9tXvklq/SxBL4BIgFNboDC8pllg8SmYxg5WNMhXHZOMKlmsTdDoYszm//urriPUJhaDFkpxg3h/z3pOfolUXCAtpgtgVNabHM8wUj5U3y6gRF6xTvvvaDSJxkVgxR9IwiOl1Dk4+Y/+8wdN2l5ejFqd4/OTJoy/msQKNIFUlkllkLqVw1ShGfAmvOyHi6VQrG3TrE6RoivXEAvWTEelUjIuzPSbtJoF1KSgJFRdJNxFcj5XVKkrKoGNJvLiY03NV3vv0kGmoIGfihJqEIRZJ2CqvGCmqQwfDunxHuqgR99Nkoxay2cat7aEpDum1JbqazmA8ICYGVLdXkStpVu5sESgWI6tN7eUH5OJXv8xlbiGGLkW4vlogm4xTTqssb2aIbaUobelUogqTZp/m8DEvH3xCLltG1GTadpTa2RQAJZnFtKaUb94hzC0RyW0RSYRk0h6SVicl7fP2psfmxhBz9IxAaZDRFVJpjfbI4bT2uR4/kaAhWDgZnbYwJpaPkM4Mef0bb/DCr5N8LYW2naX89pC+dUbXG1APJlhah3YsxYvh9Iu1jfttlrILBLZP4EWopDW0WQOSY9reKdU7OSorCtbsmOfNXRreECuuYC9Wed68oo9dNcFsCnOhzIdPDmnsNrmdWuZmvkwyyDM/HWHunXEzu8SWvEDBNdh9UcPIr/Dw2QXl3GVjmrPjl8T9kO2Fde5vLZAXYkwff8bw8VNS4ZD67gHfe+M22/kcCSkg7lnMmxf4E5vjxjGd3hU1/svGlyIi6HsuldiEx+dtvPYAoVJFL62iKAbJUhT34gWJxTdxDYvT/pSO2Gc5k2ByWAdRRbQvQ8NSOkk8nuH88Jx6KHJa71MurBIVVpnWDB5MRxSZ0kfixe4Iay5xFsmjJzUqGwukg2XgXwGgL5VwQ5XHL0+5FouxsX6DnzdsAi1NY64gdmc4/gKrlRyyfo2Ll8ekXqli+VPe/v3f5/h//BEA6WKMmTfCCiIoksZk6rK2qpCsZFm/tkImU2Hu1gmEGEY6Q+O0xZNuD02TSBgyB88vxTKJqE/ztMFX7xZJ+hEefnZAulAmMgsZOSZ+oLA7neNnJAKzjxdK3K/oiPMha2urnH+OcXu1Om6vS8MdUlpYxq/PiYlJ7LGNPvXRy8skXYtku0VCDTlotpkPZkyP9sGU6dauTpaRoLBTe0EQd3l5+ohZaw81a2A1JyQWV1EyKnNJIl9aJuqck7Vl4pkIs8GImBInmr08Oc1xAiG9QrtxRkSeMxx0CaJjNjdMqvkDBiORgXfIYDbk1Tdu8PFRkccXMxKjPpF0koveJX34+tfv8WJwjYkzQQh8bHmT7D2Nzzp17n31Gn7EoBjXcaQcC7dfxRzr7HZb3FhOcdp1yV+/CZevG6O4SWDnKFXiJIIznLqObSVYXDfYzhUgVNnthMh+jrDRpi6ckIxEaI4ElOhVZNE4rzO5aHL27CnxiIhWUDGXBqwlMvzZoMHpw0O+fus2ou2gJfNInst80GZekli4fhdhfglOtpShd3zIa28UCQSBeuuE8PgAezamO1nm1/7R7/NOvQtyGUeIsvPBj0isl1B6Kooqcv3+3wJl4SyV4dmTI7Y3dWoYyLrD9RsOD3/0PqEoUQ37jOsNlu5/m5HRZ+n6Xd7/1/+CxdgS8eoyhbW3AGhJUdxslbOTGZOkzI+eP2QhJvCa3uLoZx9TKHbpCDIbN+MMpDhPmw3yX3uL43mdpVDHCK/8+GKLq7TGMsqqjy3G2WuP8IYOjiIgmQp6epv4bI7mW8QySXpVmzo+ljlGVq5aUD/7+CHG9k2UiI7kOsQ9h929F5iaxlGjh2/OuXvvPj99511eDNswa1LKLOKHLqIUcvr4sgx1tVpGa7gowxTufovNocqTByes3t0m7gV82uxTtnv4FyqeI6BXF4jOJXL5RXqTNsXY5an5+HTAvLVHaDV5+dc/YmFlmfuvfYu93gWdk4DNiEEqr2EOW1zsH+MrHj/70z8l7DXYMRUe7t3/Ym2d+nNihsS7jx9RDx00e0o2lFnPaFRfX6E36FK6fZ3YzMIJdLbuf50fvn/OWjQkm4gx6l8qMK+XNnnyfI98Nka56qKrBwhGhELUYjkhE9XizDoLDNoW6eVVhk/bhJElTp02KdOjVL4ElPrQ5sSV2KgW8CYD5skQ92DOO49+zp2vpxg2+xQSacJWivziJn/y0x8QVFd4dzJiMh+jVK/szDPJZdpndTSxSyYT4VyHue0x1UMOGwfkKmv4qQwffvCcWabK+uoNBgMbe2SRVJe/mGdxPcs0L3LwyUskVWXqWaRzeVwcvv3d3+F58S633/oOquTQ3NvlJz/4c/xCiUZ9l4W1NKnPm6CK9oCbW9cZuCKTjg2ZdTK6SFWUUGSP9NIWL1sX3FzcxDrosPzG1znsDzl6+gG3v/Y6tdO/BX0NXtYec/9GkWlzh2QyS1+c884f/QlHp4+YFiLM1R5byW36F1FUkrSPW1x//RtkrAEXkx4fHV02Qe3JM57u/hVdT6D77D2CZAkvWuC4Z/H3lxfwTy0+PfyU1zZ/j+npYzbXs/TFHYa2R0u7zis3Xv3imQ67DaKZBULZZNiGqBcimxJPf/opuXARLROjVErj+RalG3dYvrvBH50+xkVj6dYV+kaNDJqXRJV0FFUmmPRxiVLMZhkfnmGvLzAMoGzo1FstSqGHNRgz7HVYVVW2c3HeA7ILFc6eNhjMBTbcJNq4RSmT4+GTOo4z4PXsIqORxUo5w7h2ihiJIVgegbRCfqOEIVwm+Z6NJ/gNk8OfPyE6bzGdTYiIChtvfRdLV/nk5zvElyOcjGtYRzssVOJUYlU+3H1BWMwjGlednquewIP6EecXXdxqire//grxeIRgekbdHfLt127y4OycN9/+Cu9+9CFH+wdoRhRBS/L6tW/hfn7taQ+bTEbgLSTotp9wZ3MTJzzjWrbKdNzEb4QUfBnTifDgg0O6Ty4QDZH+YMjKrft0P7f89jMSVtdDWcqzEt8kMncYREW2klme/PFPubl1m7hg45khY+GEb2/fRSiX+ezwhHAqEzhXSb5JX0DObGD25zzd/5C0nkBb3OKJV2T53j3UWI53//IvGBWy3Ftd5cF7D0nnUuQjy7x8erXpxKCLrooMJhdIgcaw5rK6+JDvfO2bxLwquityfX2L1u77jH2fV772Jh/vfog9d8kXKqSNyzzK/cVbHNW7mF4DN5BQHItKoUAoOBw06iTqTzizVPT5nOdnL1EUhYnZp5LNYdVHfOX2W79yD34pgOC83iamNLlTjbNatjkeQOGNO/zl3ntEBY+K0CegydOPfkLltf8Yb2IRKxVQ/CiVcYwP//o9AHxvhj3r40lRBrLMb/3uJnKosNFxcT4zCfQG3/t793n5/IeU1wOaWpuUmGC/P2Ln5S4nT15+8UyJfAaxoHLRtLgbDTGHbUrTJhtiBPnsMZuZGzSeveDXvvdteuE+4VRhM+3zItR59On7X8xjdTtEI2ksyeR4PoaTUxLJIutrr3I8rqFby7Q++pCVSpq86dA4aRGqTdavrRLMmoTe5Z38jfUtzFSS/f0IKSOLG8r0JiO+sl4hpS9xNhlyRBktIXHnrduEeol2b8bO0xnT8znXvlcEIB1J8/iiQ6xSZokcPVfjqGty8NfvYRa2+Om7P+Ldn8W4F/EIxQ4f7Ta4sVHFWHgdIV5Bzr8F/DEAmVKG277AD95/wc6H7yJubNPyHCrFNRLJIp8+fMbyq/epjVz6E5e5H7JIyOmDZ5wad/HMy7t0NLmGlniOKjm07Dg/fLLPm9dGnBxF+K3lm3TDEyolhelsTK3tEBHK2L5KKRZlWRvyYvcyfE5lr1PIixiiQG/cZ9boUrZPkbqnfKN4F/Ggzlv3N9GW80QrGs+7U9L4jBcqZII0f/rzx198t8rWNZzRGCnMIUdegbjFNGKjVkpE00UaZw9JFK/Rujjl+VmDxZV18sMO+xdHdLpXnpUFNaQ2aZNYzFBKJlmyfHS1RikZ8uHBj4mbJrs/+z6e7LPXOWM07bK2XiRqjkkqXSLypWdDs35ERgqZDmZU4kmG0wuOs8us3Fgnmi3w4sJEz4jYooIQiaGhMjp/TL6Q5bxxwdFZ8Cv34JcCCCzXR0pnCG6l6QgjJqMDTnabtGYSqeYQP5PnQS/g/ne/i1haIpNTGZk+LX9Eb+eQhHxZvHLenGIsrNHZbZFcL3Ma91jJL5EsFelMa/R6J5x2zuh5dW7cWGFVjHMwtJEiBQrxHJn4lfBqapqozQE3ry0y7fVY2lrglljCCU7Yb+5hv9inZMjoGZ9rd9M86jrcTWzQt1oUMwX+P0Ovm7kiO/tnxPUc18oLaLcr1Pd2OfubDwnDOLIvMrVtmDrEAonnwxGyEWfSnbC+nKV3cWmUEou5tFoN9p4coFY3WVkosbW6gBoNCPwZTw9O2X79DppVwxEDOiONZ7UxQzek53Z5q/I6AKaTQC3fQbJOGUVNlgo5yne+wafv/BgnEFCyeb73D/4R7QfvEBWKLCVFeodnLGV03r8Y4Teu6MNPnu/QGhyTp4EteRz/9Gcs3t8gdDJo7gKhU0B0krS7XZrHLiuVV4guqmzESoTylGl4WeTTOHtBPtokq11DmckUq0uYjacQhLz70QNCU2GYfYme+AqdBztI2gan9UN++7e/idU/4vZNkR8DYjjl69eXWFUiKBGDs1QX49xnQcownnootSmHQYfv/MP7TCYn3EpW+bA+wxZtaq0mK9cW2fmLy7WpsQjS7jNeWVJ4vH9B2nI4r7eJ6jKjwGd+0EJxAo4OB0RHx3Sp82LUQlICAu9KR9AatpjMm8RyOlvVDOHUwSgL/PP//Q9pNvtMjCxRV2E+6jINLpiLFpHsKktTmencJ/jczq3tC4hml29uLaFbHmIYcu/VOywV4tRiaX74ZI9YzaITqVHJ5Hj54gO2b97h+ckJsQWJILgCp182vhSsQS6bYaGwie8pOHKG/lBlbft1qrffJhlfYDwWMSIVXFfB7PZxug00wYPQRUjE8IPLu+ZieRM9iDO1InhBjFgmQ2fi0vd6WJqPslrByqVY3FhlMJ3il7IgKnSGJqGvIGhXtE+pEEWJpXDmFhIujWmfUPKQlARevopd0DGqBVBt1KiKGww4+OwzRMVhZl5ZntVPGrx8ecp5p8G03yT0LVLpBPXhAN9zePDkGSPX54OzFufOnKmUoN11OTwaINgRBqeXJhcjSyFIGQwlicN2l/5wQrN1ji/4CLECxeIKWU2j07OZzmUOmx1a4x5da0YQ+Bj+JeY7ExsUgfPBlGi0ApqA7dpMlYC5JvLN3/uPmJYlfu13/x7peIKEEmFzYZFMOcHW8jLm5KqLz/nOPs6oiSXZTCdwb32ZRCBx9KQF3TEZPYvdcDl+WcfwQJy1sdsziokoqqERcqksT+cSKK5EaM3QXZe8KyM7Bo3mmGZXpNMY8eLhKe++/5S9Xh9XDFjNK4gMsD2fQury1EzHsiS0ODPLpt+zOPqkye7zAb3TA6anHsXlCkEY4/i8hRjJ0jTn7J88p9a5QA5DbPlqO+yc1pj1OkydIRcXLcq5DJVEEqs7we1ZVPQ8KUFjyShgeCJO9wymfTTXZnx2FVlKgU1CEknIISulPMVqlfp8wv6gxel0QMM+py7Z1OcTlGQCqZolWa4iRjPIio4TXIJlczBED1100afbb6KKBqHn4XoqejoHk4B5q8vF4UtiEY9SLETFpaAmWcslUZy/BTqCkuEwDluMByLKxGXr138H2Znwhhrn6B0FPa4QL24xNidcDPYY2EM8sUQlt4yQSBD/vLPMsD+lP5iSjgi8HNdZCqr4MQUpTKF/Q0eYT/GyOqMwzUAYsf/0lHxCJBVbYnLWI5YufvFMKdPHGTfZPWiTzxq8Ut1mpESZlGcIszLPHv411vIKmrnKk3f3Oei0SS8WUVUZP5/k//58HssLWF1cRVFV5sMJQmhQKqic+THiuSzt/oy4tkRU8dGiOqmyjGy6MG7RPJ6Rra7Co89YX9ugUJ2ydEem/fSUH3x2wWbRIDw9IozFWSgt8oMff4imwCCV56NnL9m8XmXsDyjfXCKXveyY04vZCK7ArV//CrFRBy0Os/ARy6s6Pf+Qb772W+z2RyyVVSJrGTzFJ5tYIepMuJa7zZ/+/KqKbRorIvVOueg6pNdeQ8iWmVyMsaYxnFmeeCHPy0czcpl14msBrtzm7voS89MuhhSgG5eRnM6M850jvl3IE1dj3Ny8S7GfZdyt0xlLTNvnrN//NtbMYyEGb2+WMXIyT8czFFFFUy8juYvjPs60ybImcXC2z7TV5SubG5w+rtPwKlBco3l6Qtg2eHDu8mhwRqmUJCr6rFzfxpga/PXna8umC0w8G2sKlewqxXyGmVzBqh2TTieIRkSKbsA/2FjhJ40jtGKCbv2CvJxmJWawN74E8MW4QddxEGNx0pmQlKYzeT4hu5nGLI6YhzOiNwR+vvuYzWwZKUhQHzrc2LjOzN6lZl4mnl99fRPz5SEX3Qmp5U2ODg+IHJ3iuBHciEIkqVMpplGDKZLskFpfZW88JVLNMGseU6tdeW38svGlAIKdsx3yr7xOb+7QHs9IFkVsO41i1VDXf4PPPt5l6/4tRlOXubpKdVFDmJzizAXC6Zz25z3rfAF8wcU6eslmscTX3rpG67SPPTXRgj5D3yS1mOPO+grRSITu2TO8xpR5fUDgRFH7V+47jfN3KKbjEPNZzEZpNz6mtrHGzLlAjlxQeK2Ksb5KQ3IpJALU8zZVY5mR4tGaTr6YJ5NLUpRU2o5EOHcpruTJJUUS0hxF19gqJZm1+4S9NoYeUi0XcCcuubVFmO5QUi6jFEnRSZd9trZlCskSLz+u8bCzi54v4g4mOKFFOi5TGw/w+y0iJYPcq0WisQyF5RQvW5fKwqOzOpPaLv/J/d9lEPbJrGd4sdcgps1YeeMNHNkk4lgc/vRjEjObSmWdjmXTcwSe7p5zOm58sbao5uFmMqwIMVbyMvn+BdFQpbq8ws3ybTRxyte/keV4MGY6q9P46BGf7H/Kcuoa0tobnJxfUpFBs8FXvnaTJ40+nWaHO2++zjSMEFGWMeU+rX6HJ//+L1lerLJw96sMfBicmjjjMbLtEs1fgtzB+IxqKuDp8IzFXJRKzKNW3yf19iK9I5UTRWQa80D26HbmLOdThP6AmFrGabcYDq6iHUUViK8toSY1KuacUdNBi+coKwrytMfgpEet8QQnppMUBQbHXSq5EoXECv1ylL3Pr3Sy76ILAYFt89H7R2x87T769ibDk59QWFpB0gIeNIekF8vkVxbxLI+TgxrpMMJiNYYRvWSyrGYLIhEeH3V5M5nG9QMGI5ej80+5ubGOGDiczyaUs0Xqhko6lSUlJOj3z0luZDEOryjNXza+FEDw8uVP2WyvcNLZYfvOOm4wZCVT5INjkWvlFTbfLtPpTRg4M2xxgDU2Wc5kECMiyYjFWmzMx8BNYxHvdML22l3mORGnU6eQ0qh3DsjJDhFlznA2o9azyad14ksyZ2KUuNciquv44tU9ajUNoT3iZjlGJAcNuc0kGaN63+V6eoWdZwdsb5R59PwRr919m5ShouREzpoNZOWqZuHmjQUi6QyJZIFnew28yJShFOHNX/t1tMIiJy8fULi+hNpvYDYuiC7kkCIGCcOgfeaSDuPAj/j+Ow+Y6hOU61kq6+sYy1tM52M+/uwF+2endIM5edUguqggiQ4ryyvEciGaIiKEFo3+5afeHQyolJb58ONPuF/UwJSIpGTiRhrVsjk726XecoiO+yzJOspwyPzignE0Q5jNsrx1+4u1Pfv4ASnFRlINLGsOtkRCl1AjyywkB2iZNJnKAkF7h7rpslLcIIiGpCq3eNnuYWmXYe9E9QjsMYuFFM3mhA9f7JJdqXDcf05p9TUSSoNvV17BSOYQfI1BEDD1p1jeHLM5RF29tHxfjI/wBYe3NvPgzIinl+hVBqRyCeSzOlNBwjmOsf3VVTRBxepNUZ0uj3sGO4fnmL9Qm/fRk/e4njL49LNzbmYTNM48qnerdPwz3LaDoESoVLaIaklEC0qvLfP8oI7r6ITGFX2cyJfQjSyum2E0b2D2Ooy0c1zZRw0hY4bockjfjzJtOMgSXHRqrBbLyOcdpoM6AIbhoxVLRONZTs0QQcgjSg7xhIaTVAlnHpmoxuy8zYk/45E/5c03v4WiKxzXj5le/ZK/dHwpgCBs/YzBQZFr22vkRZugvc/UsrhTTPJ874joeEwQlYnrMhlhgj+aoAUCgTNk1pvSP34HgFHnhHbtlFJpGatlohUy9AcTBDEgsEQ8K8b45IhrSyuIdpf2RYinJ3HGDptZhVnvSho8l5sYnoZp95lPuwTGmNPGpyxXolzMfC78C+JCEnXD5+nxB2xfrzKejllaE2gfXdl5GYki7U4fL1BZXssz9V0kxaB2/IhNYUpgdnDMMercRlSjWPM5Jzv7TO05G7kkUeMSyf/4Bx9x53aVVNwlErcRtBgLRoHq7RSt8S2G3XOIRaimYghmjNTiArLYR3UtWrbD2dMLAGJ+lnh8mc54l/6dNRTd5cKWqAUmf3/zVR7sP2QmTVnZvoPZnXLgSbSVKMvZIufjkN4vgJypaqxWrtHsnDCp93k5PGJraw1p7rLz8CF3X/9NnNoUd+KhEmFFTdNwdBStRHx2hKxdUpGlhQiDUwfPa0O0x9/8P3/C2/dfY/n6BnEMjmZLzCybzqTFWd8klokSjznMLIdUOSSIXN5/Xxy+TylcZZKME9o9hu4cU1Vp158Qq1aIxm1ULAZ6nfn5lEg0iiSYtBoPScdiTMdXkdx87jCLpwhTRYaKR0JwuOg0eNYcIYYBN9arFCJlPjuoERHzjFufMZkPWFxf5XTn5It52nsvGcwClMwmpyfnaGGH0NdZrKwzbbZ5flQjX3HJLkTp15vkKmXKlSJiOELu1VnJXGb7xRDw0qQW4jROWuQWF6lsF+m1mrQGPR6cHPCYzhEWAAAgAElEQVTV23eYJTxEV8eQFexOF0U0iIgK20urv3IPfimAYLEqsZAbc6+UpTu8QM/orCbKvDg64u21CuPWkKk4o3/RoVBeJFDizNUBFU3imd3h1Xub/PBHjykn8tysttisbtIYt+mfnuGZM2zbRUmb+O6Mr7+9jj3uQqCwUkrTGswYx6IsVeJks1c88qsbVQqJFKHXh3BAXfTJJgzSiQ5SGPDavbv4okxjZ8JiNU4lP0OXA/RoDtW/SjoNxxadVpeJNcPCJV6sEDM8nPkYLyhjqCFx0aU/6SCGPs2LMwbjEaIjcTRsELt72c5r5+iM/EKBxviQ3/6t/5DaywG+2GH79TxVO0J/FMVIZhnXjzEUmdb5U/qjNsVMgtlkzs9/9gkADTWCL0kkDIOjepu21UXVdV40egQ/e492r80s6rNbm3E9pqIKCQZSnMOaTc8JeNy9Arn1hXvYgkwmbiKnSyyEGiQSrK3cw4nHQUzy8EULUfEY1V0agYdgJBibBr2RQ/1zKa7Ve0QsI6LaCuXKIku3iqQzKYJZk52TU5buVmgdPiFbWSXuNsnoIrH0Ion4EQYq1exljkj2ZsjSgIvWENNsYqhdFEMnzI/RI3P2ZgNe/Y37fPLBQ9xhm1UvRa3dRZZ8rMAirl5RbAupKGFgo4kTPNII8QyR5Iwbt7axoypzR+TjZ89QI3Fqbp1aL6C89S0mUZXzWf2LeQbdGqFssJiYYKU9ov6MvqRhTTsUkg4lZchXl7fomhM82uiTGQksWsd9cktpMp8XMCnxIuedDrFRg82NJaZNi+bpKSjQGx2xubhAqzUglUmQTyg0RnPGpoiWzSEYQ3rBlbPyLxtfCiBQJ/D4o+f4Y4lSeQPdc/no+c8IxiPOBu8heXM0XeD4sIP21j2q+SwPH36A5EgUIyGPX1x2lnHEM4q5NJ3OPrLqsZgLUcIMA0dibh0STaQ47Q+5tbZCb1RnZIUM5gNsdcpxH8bhlddgrhwwaTSZuk2yixnW80WWb1SoXfTR0RgFx7hTicK1NMNph7M+JHJ5as0nhMaVQs1zpkiRGYYssL6+wJPjU4Z9G90oQvsl64kITq9PThUZDJqkJJeVe+uErkyrPaY3u8yst857PH50RCoLP/iL7zOZDCjlE0Qii8ysACkWQ8EjXciys3vC8fkZkm1zcNrkuDnCH1+GqzZ9PM/EIeD5qE1WkUhE5iSKOvvmlLE3IkkEW5jys6Mpiqcg2zItJ6SQdLB/Icac+zL1TpuopLCSW2EiiMznMWx5gU01y7Q/IJ2UMc/HRByRgS0z6pwRejLWXCaZKgPw6s07dAdjDts+s7KBJ4VMLi6QZYVyqYzhw431txiLLsUVA9macHO5BDOJW6sFzPpltDPsvSRaU5nabUzBxoqExBbGaHOTJ0cHRLQEg9OPaE9Ehod9XgQRVqtLTEYDTlo95rOrdm6nwzbX1krY8zGt+pjiwjLW+QDB9rGsERf9Ab4f4HsDbDdATFZpDX0Ssko2v8Dw0liI+7dF1DAkjDRJrMtMRIdXqhrDkctwPuEb39pmOjnjzbeXKadkHGsK/SFm1EIWZ6BdgpOvRFhZShGGNqHlkMjpuLJAPJeia3bozmSCUGMtvcBKKcbS+j2GoykqAtmMgXz3jV+5B//Ooejvxt+N/5+ML71D0cPv75KOeoRBQE/xaNXqlBMyUuAw8kREJUBzTQIpTaQQx3MCTndbGIqGojhs31pn4c5t/qv/9n9ldnxGulrBbnRpDesUtQS5xSqh5zGY2cQjItawSyGboFBcoDvoMq71SS8kmNs9/rt//i8A+M/+m/+JeNJASyaxzTnWzCS3UGRaPyMWi2IyoZzLMZz0mbsyoS+yun6d2nCCQoT/4T/9HQD+3Y9+k3L2Ho7vkk3E+OyoT7pUwJw0qaQLaEaW2uFjnDBGoZJEF01OTg9IR1II1gEPfvKIf/K/TLi7Dvdev4Pd6YPrU6yUSZRWUWIZZC1CGAR0GyG+Z5OKRRBUk/54ghBaiGbAycFj/uz9C/7VH/4zev02yWyC2mGLwuJ1GgdPSKZUPBIY6STjzgBndEJKi+MQJR4Paew2MWIuoSjzT/7NJTm6dvufogYmdzavs3d+jBoNiEfTRA2NfrtJVNCRsxqdnk8iImAHHtVsnLN2j9HAx/VMDl/+Ux7+23c4/uwxuVSGvjtH1/MMpxOs8ZyaM0ec2FimRyColFdjWKZDtrxMQgywbJ+l7Qxf/b3v8F//y/+Zft9FHE2Y1hpMHJXRcMR4HFJIxTg5OUWY+bhOl0oqQW6hwlpa57BrEltZZHV7iz/4x/85AP/yj76DO3Zx/QBXLlLO5plOBpx0+iTiOrqWw7JntNozlIiIGgkQwxGi5DGs7/KHf3B57fnv/4vfxdBkZBvurC5Rm5g4loooRfDdKZFQBbtDPlUirwVIosuo0+VkMGZxs8rO7hH/5b/5K/7xP7vDG7e/xk9/+AHHosOyVGIkyhQKBVayFaSkz/7xBYIo0nNmyEObW2/f4/DRHmfdE8ox7ZfsvKvxpQCCJ8fvsaQnIFlld9BhEE7Ys4donTGJhTjmxMVSNEqpHGbnjDCAnfN9nPmcZDKJkrik/TzLRtQDrMEYUbRYW91gMu4gBC5qNEIpmsXzBHKVLAd7F7TDM5q1OilZYNgYElOuKJa3v3GbeNpg0O0TTeSoTTuks3G8fJqCAplCnFDVGc00Luo9EpEKgd0jikU/vCpnXUjfJhbmmXkqozOTkpIgbMXwhAIXQ59gLhMIS2SurWOac+IFlTvX1wjwqQq3aLciwI955Su/QzwmEpJhIZUgu3YTSV+n1h1yvNtAkhRmskJFEcjlC6h+A8NrIUYMcqky5WKZP3v/X9Pu1Tk+7cFJHymRYFxvIgcRXu7XEZUhGbPEfCyQSFd5djEgnRaoj3xM1UKdBkSFX7hHZ6P45y+wT2bcyMYQIwLmvEUpvcGdpeVLc5VsmoElUSjm2G90SQc2/VGXMJ9Aklc4fAnNeoPzoUVHmNDTDHy7h+dBq18nnpboajPsSBJ/NkcJc6h5kU+bz5GnPpmITvi5DqzVVhhPdBgGrG2+xuKkyygWZdgeYyBy7dU3cQINp/Wc+qBOt94gW7xOYi3JTJBpT69KdYuZa2gJFcGJE8iQSubpqAGO3cInIGKsIKkdVlMqQjgnqguowpyldIpw6yZ/+Af/GwBRLYuLi55MkqissWQ7fPTuLhE8ojENMUxTrVRJ5A0OPtrFnLVIpBNE4gLzqcr25mvAXyGeNBks1VFKWW75SeZWhGpMwwlzBEHI9KTJ8KDJo5HFf/C123iKhzOMcfgYBL/Fu8NfrSz8UgBB6/glykKV44NndHCwjSSxhM7Sks5AnKO4M+SZiLRURR/5uLaLoUvM+y4Dqc/zl5fJuaQE5wOH/uAZi9fWiEVi3H19lXpvytbWTcSJzCxwOHr+E+Z2B1XRiOsq7c6E6nqGfvdKRxBYu6S9TZRwQn+/h26IRGICnamJ36+RMlaZ1DvUzix6tkYgn7JQLlPUbaqFq/4I7b6MmYzhIdMzVVr1BuWSwWyks7BY4mjeJpZ8k7PDQ5IJiag3YYDIdDyimRAxomsAFK6/hSKkSBRbBNM2E1dmcHTI01qIJBic9/ucH+zxm995hd7eLsvlDIVUldZ0RiDGEDOXhVAbK2sMPZla0yShaShRiXi6yHm7xv3NNURH5kjoYVsO5XICTQ3xc3EOZzG0nM6wd/WObr1yj5F7ytQc4/sJ1tNpfNXh2noeR1Tp22NULU2xqLNYiHFx+BAvCIhoAulIEk+/TIQd96f0NRnLHXB2+oTWbIBaXMIyj4mqkE3GsPqHjMwAL6bQGYnsXQxJRDWGZhv57DLilXyRvcM6y6mQ+tDibl5lNZVhbzxie7GCO3CodWpoyYCj5gWhpLKz9ynPZh4r6ysYmatTU0mv0O86RMUoteYxm0GKqWlTzKzQ6XUZdLpI0QiFaoK9z+rkcjqeZdM5rrG1fOViHHgacmiwtLlBXF8hEEPuXjcI1TJWs02328b3CjQOe/RGDoIboARtlq+VGQQBjnt5a27UIN2S6e6WkUYD3viNb2MSxRc8/o8P/09WEyvkb27ydU8lK1TwHJvHf/6cf3jvK3z/Y5Ob7q/2LPxSSIw78y71+QRT8EioMtViHM+ymMx9ZpKKHNFQdJHxoEOv18R2R5i2x7A3xBr36FqXySLPmzHozzBycfwghe+4zF0bTU5iSDFk3WDcnjJxTSKGQWA5RLUUnmYz7Xs43pUxSXkxg6rLLKZS5GWRVSWFNlVJijqiWKZZ85j2JAIzQmQO6kzANR0ilocwuZJzzuYiCSWGJiXAExADD8+NMTNFaqc9xEBHz2UZk0IWUgzGcyJaDNe2mE0d9PzlZvFNmbieIhpNImWqXDQHqFrAUj4go8+ZT48JmTPzxrj2DEdS0UulS92+J1FJXaomPQRkKU6sVMTIF1AVA18ISCcyBKGM6E2IhAKyFDAJPIYzk0Qkh5EvM0NG0dJfrC07G7CYNkjJJumoizBsI/kDtJiKns6g4mIFc6KGxXRyzKRXw2oPMTSBvJFG0y6Tc4HjoCVydOceiUKBSDLkonOAaISgOYwnpyCHpHI63XkbIe6Rz4n0Jj06ownz2SXtO+gOCYKA0XBK62KMLEeJiREquk/Bm7MdmVMVBmQ0j0ImQa/dZjgb4QoWvUkf3/W+WNvcDrF9l/Z4hhRqWIGDKIaYoogXhATWlNCZM6iPEZGRIir5ygITZ47tXDVKMacmU9NElBWMYpnB0CMgiTuSmEx8+ud96pMBZmCSyKaRo3FS+TRe6KGQIPAvQU5wDZayOWrHT/ADB3k657CzT3vQpBBdQslukBWTZFN3SCeSKJYMrodvjrmWzTP51TVHX46I4HTkUvPOEOOQJAutPZZu3KU5G1CN+zR7XRSjwHx0QWv/BeYEWlMJNWJQNy9QRpfa/mBkEo34nD2rk0mdYaeqaN42d67do+AMmc4l5KJMfddiubKOGfSYuxMSyQKmE9DvDr54ppNag+2IzKx1RIUFTl4c4ugxdC9gNlQ4PBmgCwHqxGLV06hHXOTAQisYVFJXNQuBJnE4qxOJVEkWy8xnAzqDAXNBJpvZZDIdsb68QmvW4NNWm61snnlvSCSZoTns0q3VAMjpaXxXoDGPYdsDDvZmDCfP+OZXryOEPba2bXLFLE+fvcdrd+7R8lwyFlRKy4SuSL1zeV3pt0ZMRkPmFkjzJudjn+uLVQhF5vMBbcclm09zMZxQuHYNRQ2ZBHOMfJ7BSUjz4oo+LC9kGdcdioUYiuozHzlEJA236/Dh+QvKK3kyaQ3RjNJp7FDQ5ywubLEzsOlOZNTIJbvy4LMdtKU4/UGbXFbi8OwBhc1VumoMNa3SOWqwlLVQIgqj0RGNB3PSygYZv0QwaCCVLwGllJQZjUXq+21uLEa4vfk9rqsu83SH2ctDpr0Z39oq8t6jx/hDk42V1znst3EjHTTB5eLoqny4PZozsS3U7BKznQnRqEXPn2IUBLRqiGLJlEtJPnlxQFsNSQVJIjGJxZu32D29On0rWZ3AU9jf6VOM1VAcyGaqLK6s8+d/1MFyDD547xG+NyWjq+RzaRASLOsSCU2m17v8l0bxFD/6QZv4jTcwxRVq3SZ2ACemw9tf+3XuvfEKf/Vv/wir/gxJmlAYemwm5nz/Jz/k1Ve2SC2v/co9+KUAgk7rHLFUJrBDngzbLN64zflHe7iGzmQ6wXUjzNpP0QWdQF8koQZcHDynWgqoZDI0WpcRQTYZZzg3iVhTFlMRfMuhe7KH/ModcmvfoLZ7xNnBHu1Jjt6np7xyPYoekThtTSik0/jlq+Ydhhbl5GCf6CxkeL6LctAjG09yctEjtXSTtbSI6Af4jRoRNQ/pBJVrd5gbPmJ4Bb9zZ0guJxHa5yhhkSASkllf5mynh9zvIE/71GYXtEcOYsSi5k8Q+h7VFQMpPSEyvIxSBKIEgUZSE5lEAtZvzRm19zkzn+LqNjFzglLJkzA0pAWfTu+EpTHMRJVZYJBNXp5S1mzEaDJm6gqk40kyCZ9Bt4ZcWMArVzAUHU8v4B1+wocvTtGDDl99YxN7bpGMK0gLiS/WpikL7B/38N0X3CiViIoiidwaoTcmVEsE0zbn45B644xC1CXuJckhYh+32f7KN4ln1vi/gJHdRHEMVlarPPjsY7LZZS7OzyFboGPZVJbLTMwBSXtCRDZYKJQJGmNe3bxJMx0ns3jZ+3DYm3LR6lFMGaysbnA26SAHbdzzQ779yi0Oisc8328hr6zidx4T9N6jnK7QH2fotxzKv9jpuZRGcWxmjS6Cb9MWwQyGDBr76GqUqJpAz8ok0i6tHoz1ObLrUShlUX+BYq0fzUlk8viiii8JrF9b4OGjPdxkGmn1VeanRxw8+oSOL/HmkkkivUW69C0qr32dp0efko1eekQGRkBCsfEQiCQ9+lOTO+trLE+bpGufsKi1ecM9J7t6jcCR0FfXaO8dcD3IELgeQetvQVv0/bMGguViSTIFPcHxg09R1SLJksJgnmA0qeF3Byxvx3nvwQnpaBRBCmkOL5gJOWb1ywytOe+Q02Nc6AqjuU01c41MOoPd0/h3f/4UPyPy8FGLw6dNtFSbncdxqtdUFisFas0xtnd1/527EoacZjisYQ1Mdn74Ib/z9huosx5RB9ypREyUwEkQTG2ySxnCqY8fkRkJVyHm+kICTY/Rl21awzn64hJWNkVmwSCrSAi9PMcf1Jk4c3KVkKjgoy1DMj1EQ6UqX5a0HjUt0pE529fLtHbqzG0XdbVKUnIJvDbLXymwqCZ5cO7y4VmduL5M7bzFUuEuWaXAYe2S2A58gVwiybg9ojnxWFtewLMcWudzporKa1/dol0/ZiUTY//wMxRDZNJqUiwvYAGT5tUPpal9bqyP6fQzRFdL2JE87+0/x28NUcrfopeM4jrnaJqCori4zUd8+NGPiYmLCAuvEcldSoODXAITD7vf5Y3tJUJF5mHT5ebtbT7p1ckoIYmZyvbSIjG7yIEwI58yiAYmmcIqA+tSI3FyWGN95VVuZGRMt0/7vEEQCUmKef5m55TCRgb+X/be68eWLDvz+4U/58Tx3uVJf/PmvXVdOZbr6m6S3c2h1UiQRIkaEZyHATQQBAEjCAIkzUgvwrzIvAgQBiPNw4jQkKIZSTTDJtnNduXrmrouzU1/Mo/3ccKfCD1kqbIB9fSraiCuP2AjdkSsb6/17W+t5QXoWh718JiwkCZVzKE+mVEr5RHDK7I4JZboT05xhICx6pIS4rRsgVv1TQqFOHkpybOdE1LJFTL2C8xAJZeOkiolEIKVL9axExrlYpqFGPCDZyekiyqZlWWeWwrnQpOHC4fw1kuIzhBpWUPOJ1CykM4pJM4FkpPL7L0Wv81CnLOUFBGyCkFgU4mluV6AeNXhz//0AfduXqcl67yz9RIPewatRYMb924STA7Iev8KCIomxEj5LqVIgtb5GbXkMjdrOfb6Jmq+xqQb40b1ZT784HukqzVkf8Hy1jK7x30GRpdobgl4ALLCyeER8YjAfKZx2F8gpXVmh4ecYeAOJD7efUIuZxMGC97+ynXG43OsQZ/4yEH/sRNh2DfonbfZTOscfXTB1q2bZKpLvKrVIaFw7EzpegskwcKy55hnU6JZh8kYFlzV7Bu+xcxYMHRMCgWVb++dU5cyvDg9ZtbVkfpwYox57dcaaKKDWpGx/SbWwiIZL+LFLgthfNfCTRQ5mBkUixp/9uEheUZsvZwmky2TL7u0D84JU3muXatyPi3gmwKqB/bMQDAvCUxbjeN5FkpExe+22DF9lgqbyN4cwZ7TOx/jDkf0Ls6RjQG5XI3pqIumGugjlZR61c7trO+ysXmTyLDJWFSYejaJSpL7/Tm1+oDynSIf//6PeH1lA8VsISShVJTwUjW2bm/SXVzuLdt4CXvW4hvXV+m3ujTyCZY38+wqMqVihVImwavlNNF5QG+vjW5aFJM602mET56fka1dymdX5CjziUtL9ZHUDJvFMrPhBREljbCexi1EebHfJ5mRySUVOq5OSsuQlXzoWEixq9uek3abi+kMy5iSLSrMBJM3b9/Dbe/jNR0GpoEyVzlfdInFMgShwNwMGbQvCNWradjShYGZENi6V8GLRnk6ddFSWR42zzicH6P/8qvs7hisSxESBZF8TiKqL3B7TWItg4+fXaYr7uwM34uSCT3a3cf8rV//NSaBCLbD9isNwkYF7TjBcmWFacyn++gYcbrghbbg2s2b2M8//ak++KUAguuv3KWcjiF6Ab9y7xXGY5AyNQrdPVQ3wdvrSVKqxPbdn6e8FDINPJxkBi1+hitYuIs0O/yf7J/2SOdVhPaYwF4wHe6zv/DQVpaYmhFGc4WhL9DfnfHKuoxr9plOmsxNj6OByUbuiggT5w6n/QlW12c+HpDIphCyPv3RgLRi0HcizM0Ba/kYZCNUbm3xZ097CEtRXrpT/WIdVfURchp1LQZyAu3pOcPjE2aPDT5+b8TtUpzrNys8fTggvzpnuSSiLnpk6zk0M+S4c8l/3H+6SyU/5rZ+nWmgoGXWqS2dEy2kqWwtUasrLKbfY69zypMnDjFcJH2ZmTdnZvgMxpeqybkroIpxcuqE2cgFr0d7rDKSo/RPDhgaceRIgDBWyAU5tNac+u0CiuQzmBkIyhX/MRm2ydTKWM37tKcTXpwcs/z6K7yzEtA8/8d89qTH12/cxPG/T3niMNdr3Hj5XZbW1zm1D9Fjlx16Qy1JNVTJiwIFWcTo9CkVr/FsNiIIBNRkgYMDAfe8yeu5EkgucbnADBtnYTHoXUYpvaHJwhsSLxSxOyanixPyKY/H5ozHRx5vpZd4JgvUTJAKy0TaU/7sj36ft175FU5edFlavmrV7kpQb5TZaRmYQZTu0YBo2GFDqnPRnrOeSJOV07S8KeOzNrlrGVbzaTRVZjy6Sg1jlkE4fMHWxnWeHs3RhgNOVJOFoOFLAYmkgCdF2B+cshIrEq3WCKWAlVqe4/vPKVUuQeVv/pvf4smHTf702y/oZ1vcm7zMvHlOJLmg3J6iiw475ik3s6/jLjSiG2nSUpTDHz6jkitTrl0NeP1J9qUAguXaGinrgrVqnrfuvYnRnRGmdZyXX2H3/jNWKmnuv7/Dzc0sainJWjrL/acH3IhrOMllLCnCnwLZVBxVDmg6LXRF5K2bt3AVjYXs4eYUHi0syrEQZSNNva5w/uKAwo01nl08p7GUxQ+vqsbODl9g+zpeCHd/8Q7JfJaz1gxDlXnqt7BTy7R7I8qNDH1Fo3syIfAWKDOLwcj9Yh1TjjK9OMMLZohJj6RYxrGjbKRKqEsiav+IoqrSD5PU0iLVTIyhV+XgvIvc7+PPL8PVWm0dCxEr1Kg2bnIv42F4C550+jjxHvFMnvpagTdy2xzsfYAelahUshzODGYzhfPuZacbUYiQTkYxOi9IxmVOmlPSYsCb924j3nyH3SenVJaKeHHojjos7DFS3+XkaE7TDxCCq4jgF775yyyc73PUK+FMWvyd/+Q36Qx91rM9HvRt/vjbY8bmnDAokX1nC7UjMg3q/OWnTSyvRUe8PO3MoUHkdAcxLHL7zjbPTw447g1Q00Xi5yOkeJznuwckPYsfNg+oxNIYkzF5weP1lZe4+PwaMplMYOXg4uyAG4UqcjBAT6ToGQKWF+G9gxH1/HXeeOUav797SnvQ5c6NW4zlkNqr6+SKV/xHcXWFUf+Ye9c3eHy/S0xQ6TdNZEUn68bAUqg2JAxBoaFHidfL+FqU4+NHzAZXQODmk5yOOvz+H34XOZHBjkWYDX2mrsGbd+9ysfuEl6tZPj4b449FDo4CNt99nU/O7pPMm8y7lweBXBaIb9T5irzEdx/8IR89+ISXX97Ai0b4Fz/8E25tVXjz59/gw+8/oVhe4VETKsklCnH42mYS8+ZVP86fZF8KIPj6K19jKTogJ0lkVAknopILQpyoCK9u09gsc/dWnenFC1bLaSorN0j6Ls/6fax4hb5wiXZD00OVIVqMIS5c/IRNVNfIJzKMxSnZrsWNeoRyLkqjFFKPFzmZOchKgJbUkMWr15FNRJmOPKyphvXaOmNmxNcLSHqJRVGk1+yx9NZX+OjpM+7cu4diJJh/dMCzjs9K5CrXVF2LdFRF09J0nZC6OEVMbNGLhuSyEaLaCrPDCV/91iame4Y0nOG5IU7gk4z53H9wWde+d9Lk9ruvki4VedE8ISUElJfrdIc2bsvgtPuclJzg/n6LsqvT2N6mNY0SiSdwBxNc/5K3eHx4QTrik8BGSdhcf3mb7GRBOLKYhI/RPZWa4mEFNoV0jEn3HOvCYRj4NOpVnr24Kqj5wfc/REn0iUbfZVjJ8pePLd59910Ozj7lxcGQ0FnhuF3h33jnm1y7d529v9ohl8rgeipOkEL8/LZn2J9RjUUpruaRIyKZUoZZt8NWoFKolvHEBb/11VXMoybt3RO2cwnG3oJAiyG1R6TUyxFzbWfEmiDTKMv0Dt9DqtRhumClVudiPGZ66CILffacOWlR4MnRQ/KbX6EuRknFU/RePPlib17go0khZt9l0Z0jOUnazS7V6iqjswl6QkD3NQr5HGJFBcnlaXufmGIxujpPmI67bK9luLa+zP5gztZGBSW+xA+ePUafykgDn95Zk/TMwoqrxKo6cqxGdHBM33Vp+5eLpZUUy7kxrY7IzZtvcLrzQ/7hsw9IpmXURIv/YvNt/tff+T0OzQocGLi5TeyTU165tsR3P93hl79286f64JcCCJIxhZgTYox6HBtNNClKevUNLo52SNUiPP/Ox8xmFnk5wbQz4bO9KZ45JZeK0567DI3L+YC5jM5yKsOFpaJFMkiaRjaWonrrJY4/uo+sTygqDn4wIZfJMxJCeq5FLb/EghBbvAqfFLYhbY4AACAASURBVElmKZ1jOveZ+3MOZjO+8dZLyOsCRi3JervM0aMXqKtFEvU6w30LQcmyMA4Y96/0CPOxhxQxkQPwhx0aK2/T2gtZblTY+ajJ6voqR5pLoOsokZBAMumHfZyZw41ShoV96XhadZWeYdPq9UnmNzCmPv29FjfqRTpP9+ie9/naV+7yKy8v8/1In0Z9jXHPJpAKDIUZY+GSdIopCpmIQtzUmMYcovEsqytx4rE1mrMh64005vCUQkqgsVxh1FPoWENqw3N0fcHUvJp9uNlwcIMMJ/0TpDDB6GLE/Q+e88a7P8+75dvEI4fMpQkPdg44n5m4lsX+hctSqY4xvcALLsnZYGYyESwmMxNUiFk+xWyF6cBgaylDt39MzRTono3JZxqcPbkgCEbUX7uHFtEYdy6bpdRqBYYnp7iqhR6Nk13eJKpblIrbOItdxgOT0soKvdMn5LMaL732Kr6ikJajRAOf5bUNfvvzvYlhnMHAJ+5AQs6ipjM8fv+Ag84pi0FIfHWJyuotVm9v8unud8hWNFRNRQ7LLPzOF+8oltKJKCrPj16w9tovMJ9NmPk9tio3mJkOkViStBBFSOTIrqxix2Ls7u9wt7bKxlaBkXN5pT2YmuztmLy5tc0HD3cofeNnaD/7Aaenx7y9fZ2pImJkQxamQHdm85s/+w6j2JS6nGD4oIOi/Ctwa3A+n1CIQ7Ih0XvY53ws8OjZP+GgOWRlq0wwndKfBahTibd/7g7OcERJkzFOmni5DSTxMqSbBkmmrorimTQKZeaDJk5E4mh/lxtv3WSrNWVitHDTNVrP/pTQtqgV1hlFJxydDVDUKyGI4FsktSyxRom5FGMSLvj2g2fcjFdoz3qMWkM6Fz3yXoaprdGbtrAYE6pzZPcKCM7bU95+p8JobpOX46iTMYZtk09vINUrRIo1AvOcUAyZGyYbYoXe7AxFFOmehCT0OgCOFSWRu8HI7ODKQ+anA9Yr61QIUSWXoQJPnwusImJLBZ6fBkQzOZo9Bz+yhpm7bDHWchwmsyFL8pSF0CHthFjSMtVGnX/rm1/FH3u0WxFmmsDB0x8iKyNKUQlNSvHZ7jPavR+rDxvLfHJ0Ttf0CBdRIskSvpTmvb84JNWo0U5tUxECwkWXw91zNu68zCKbwJj3WS5WGYiXvMXDQQshbLI7yRDptegPLsjEIhSW1nAnHcLjh7Q9ONi/IJ1fYWzBrdducPDwQ5z0Biefqx39hcRCTHB4MqNclukdNVm5VsRsm3gdC8kLOPzsmJPJiI2KSKVYZ6rUGfen2JJPuVT5YmvD4xGNQpmzF4dkNJFozOFbb32F8QubQqnE2eEYb/cFjTt1FEnA6AWIQhzHF3CmV/+RrGXQknmmgsy0Z+L0Oizd2GIhFzic7nJ3cw3PcZl/doR7cYTg1FAjaXqdLrm1dYLgknh+besWKUacd3SaE5lv/dY7JLZzNM87tFtj9k8chCCCs/Ndtrd/nXZzn/vffsw4HWMtraAJVxqZn2RfCiAwTIePm4dcS4r4oshMsejLC6QG7JknjGZ9Sokyz7sd8m0BTYzS820KKw2eTnpEVy9Vc4VYGjcXQx0n6HuwUr1OGFp40gyYkKqJeMM0F/t7OIJMvr5COleAUQTDkelMrljjiKzhmB4r1xMc+AsaSxniqTy9/jEn7S7JaIS4HaVcS9LpHHF9PY9Wj5BQJrx+92rAhdmaMjgrocgKpjlnMrNw5RJ+zOXr39jE9iTW5AwL2SCrq3yyt4+zUIlGRRbDCRiXDpyNe9xdX+Wzzw64vrSClx4zfn7M//WXz1lJxdFjBfRcie/9+UOkYpmtOyXU+h32D+6Tj6swjfEAiCaixIihR2NEPImEViRUJVx3wOHhA6LZPOW1FMPzU4SEghGkiDFFTafx4wNs/epGxBmNUbQ4w7N9fvaNu0wmHuPTLv2Zwd1qnfVonocffpdksUwuW2Jv5yNUKcEbuRw6HqJ/qdu49+Y9on2brjPjelyiKmdBkNCTHp1pFzMRxw9CnK1VlGQOeeYw8B38pSWetmfUtu4CoIgQzeSQJyZ6poohZHn4uMWtu9dpno/pjUZ89bU79P7oIXNXYxyTIS7iBypSkKQ57X+xt2Iyiep3KSgKQS6NbYg8GhxSiC8jx1UyayKNV3NcDA/Y2IzRDueMBx5m4IF79R9Zc4PZqIIgeEQKLtV0BvG8DQmRr2RTzB2XQ3PGxLIRZjGmiyF7iwhePU0m5eM5lyDXfnqM0vTRZJvlTIrIacg3bvwS/vU+3/vOIwadzyhHB2z+3N9FNbM0j5vc3SjS7YyYmS4aV7L3n2RfCiD45z/4mHvlkEXPIBoLMDWbdNwEdUFcBlvTWSg+1dcqDJWQuOyTkAXGsRB3oXK29xyAs9EF7kBmVU+C4iDW1pnOJriih2D3OeleMJ26zDTI6VVGkylzx8acOMwdjfn86gPmcnfYG3dRsg0KiQz5tSy+YDGeqCyvbbH/YsxSpY4U+KSkHIKuYHRUbmxvkcte9SOY+EP6R2e4TpSF6ZDLbVJIVKmXExx/dk45luRF/ynEL6vQ8k6MTmDjmi7e1CJmXD6Trtn4Vo+lwibKVMfoyBw3JwR9lx+1DggNh7ffjPPd7z/hnV/IM5+49HcPyKZ1uuOQuX1ZUPNk7wWaJLIoKpQ0GUnxSecj7I1fcGc7hekeMpGizOMjBFFkZJuYts1Zp8VcjjCfXqUG1xs6nz644NrKa/iRAsPBEbZcp3Ytz/GzFrY3RUvfRvLAtuck9BT1usx85HEtUSMiXa5leiKZQp2j7imFcoFEWef+j75PzUlz7+sv8f4zk/VqlQoLej0HK6XRsQ2e9g08uUBev+Q/FDzORj75XAMpkkckwfa1TSaBjRlIzF0LTwgR6svYgUb/7AKkY+KlFFFVJqldXR+fDs9ZTUs4bhRxPiVwVbKigm13eP/smOVinm73hGxjmyClEJlrCEJAIhEnmryKCKKZJJ3ZnGKpRlFTuVmv8fTJgLEA416bWBxq6QxnSprIDApEMNwhQbbI8c5zStFLF9WQ6ceGyCMNLVfmbLfD4AMDTRcZn4M0K3JmhcTnLU4ie1RyBcr1a7jWHFs8pTm1uIp3/t/2pQCCuePTNS3Smk8xLhHTsxCPoSYVIjEHfRziiiGSFeN6o4QWVZifd3HUNElXoz+7/Mkj0RwLa8wsDCnFVVzPQsRnHiwQ5jZ+oNCZdcGNYc4uQFKIRob4apIwEkfWrthew/eYTYY4ts3YbGFrC3zZIhUVIaLhiyJR0ceYjIiXk0TkCJ4AniAwnV21PPN9l1KmgWmHGE4HPBcntNBkjUZRxfYsQstlo14klCt48y5DJ45tBXiaTqp8Ge2okQiWb1MslFFNHy0bJ5JQcGcqF3sjNteWmbgBiXQWSUhx3rbRKjLpVJZ56NH6nOTTMymc2QwvFJlLIdrMxHJDYtkYYUTBV+H4rElMidAZDVkgcWL0CNJpAlNF06+6ODleyLXlGuctF3sh4/ZNXNFnTIhn+8hqBEEQQFhwctHj9vYyrXZA3HY40SdEgssinykuS4k0sjtmgYRhyYTpPH6jwN5khJXSOZ4bKFKUc89hpbiMJktkBIOxE+GifymWEaUIgjMmmk+xtr6ELujMbZvuqM+0NyQTL9Fqu6jRGKPzKYN2H72xREOvk0mXSKWulKVzY4yYXwGhx2juEI0lKRTL9MdD9FSCQjHDdDYiKoqIkoq/sJGjcQTVRxF/jCwWRXQpJKckySWzTAcBM3+MGkaYBgYpKnjmhI1yGW/qoydjJDNJ4okqSdHDWFyG9J99+heUll7CqkH4dIgmlpgNe6hhhMCwiUWixLPXiZgSyUad/skTVCFGMjAJI3PODnd47Wf/5T74pQCC2kaBjZU47qCJJXdRVJ+ebeI7AY1CFUXzmfcURhGHHc9nMXPIRVKM+n0kBfzI5QcsbV6nNzwko0aIRgOcyYjZwiOaLeNKJnptm7RYQnDmiJaA7UsYnohnyXhaiJ+4qj5rdR/z0q00Rv8Zkq4QCQ1OmydIJZAXMRo5hYw2JpRDHu2/R8VLko1JJMIu/c4V6VgprfFiFJIhBrHbZBubXMtsIktx/JgF/QXi1EecjJkHAQPHYTYboObzWK0p4eIyNBS8BKqfRQ4yjIwhicwKK4U2ZiRDLLlFIi5QSiYxihoRp8Cv/Oxvcb87Zm4LRMMRqcQlQ79y8y2U0CaYnRPOmyxvrjKYDxgLEfTWAC9IMDZVur5I4fpLtC+6+NYCW1JxbRch3wDeA8AzZsS9JGuNHHvzCaanEkRjJFIK6ZSIqKZ4fnhEt9MhXc3jOCGSY+CFc84PXUrly3v7Wm2TysoC9yLKsXdEXFrgVqrsdPq8vvUybtBhRB5FSKIVCzwe2ixXagyDUxRJRY5cgpMqlYglF8RVH/diD2OoMpfixFIya6UVAjJEhDh6uODmSzd4pGdxpDi50nUUScOfXF376qJK58LGcvOMpAnOQsb2XJSkzsIL6Xsz9HSW9niErkjYwQLX8HCwKZWugOD2xi2mvSkJxWXnk11uXL/DZv0uHavH6vL25aHRPKQiyQjFKql0io8fvSBc6Fw4JpH05VrW2cecWUP85G0kQ6VjnRA4Y8YvQsRAxRfmpASVkJDm/jHLZRVd32Ot2EIadWnUfnp94V93KPpr+2v7/4n9tA5FX4oy5L+2v7a/tv9v7UuRGvw3X//X2Viu0BQySDmJ6kaF3mBEo5RjNh6hZHRy2QjHp2dEcnl8Q6KaSrN3cEG/f0bQGfIP/rd/yt/7+/8xrUEH1dYYHhwRW0RxtQVGt0tsJUlay+CFEVY27hGvp5HcOKs31yhVGghKDlOS+Na1y8qx//I/+6e0jT7usI827zAOA5KCjaBoRNMpAnvO1AdFVNC0ECmSZuf0nFyiBK7EP/uDfwjA//J//B0sI8AeTznp9GkkKiwVbvLeZ+9TWqthTgLmRC+n3oY+sjinfi3H4GTCoPOEaPSM//w/3efXv/b3SC4VCcI49mzArHdOppQhptqEMQUvlJDcOQ93Tlitr7AQfSaWx1K5gDRXiIsT/rvf/R/4nd97jm257B7vkI+oeO6IQjSCOWiSXq4QBB7tgclgarGWLeLbLkKmgqTHUbyAk7bBf/1f/SoA70T+NTJyCr+Uo/BSnMFgSui6WNMJMyOgei3LRi3Pw8dPUZN5tutZIq7E+x89pt31SUZjfDT6Xf6jv/vfUirrtIZDqitl2v0JgaBQSSUYtU5QEjJz10SNxBADES2ZJHQCWsM5MVUgrxX4B3//t/iNX3qN6xvXESWPUqHKWC/hz7skMzKf3e/yxt17RHNZzp5+zLxnEY/auP0O+XKahT4nPQ759f/+cvjhb3/jNxBVqGSWKacTtKYu7U6TfG0NxxvgnY4prH4VY35BdNDGV0yu311meNynPTf5xh9dtrz71d/8n5l7DvVKAXtmsZif40Z9auUsOB5KNI0YFTm6OEBbJAmCkIkdkMtUcYggz1X+93/0q/zBw38fUddxzCjtwz6NfIFUPEd/OsIKQmzbALWOPTkhsB1ylRSFfAJrMkUVh0RE5yd43pV9KYAgk8lgLuaEjo45tXlwPCBc1jk3p1RTUYydU+yXt5mlKzx7PEUj4GT6lIvnJpPwlDX1UtsfDhek9FXGrV3MiY2emjA7GrBeLjAaquRzOnNrRnB8wGRWZfvmDWr5IkLSJ53XOBhdkXyi3CNin0JgoedipKM68YUAcQFXipPNZ5j1u8xGU9ZulTn47IylpSRzwyGjXLHGx80Q0ZWRow2SaZ1IvMR+Z0qpskYQUVFKZc4fnrC0vUS+oGCOdMa6iilekIvF8cgA+xRqDZJFlZP9Y4rlberXb7Pz5D7Ly5uIukDXNYgEsCJnWcsUCaQz2k2f5UqNi7MWa+UNAOaTFp5tEZfaCIsYmaSO50mo0TgtY8zY8lElBUmD0sYS+WKObsek3x+hCAJV/aqycrksU23kKSzdwa1IxO/odMeHPD/6kI1ogUpBJxJLILVjLMXLbC9nOf3kmHoyjaKMiakijCCXk/DMLsJ8yrwjgwnV9SWGzV28hYPiuKSrRYSFhD/3MGdz5HmfpOXjBAuE4PKZVq+/TlSLIMoZFEEiMnPJRPK02+ckXJfB8TkpX2Pl+j3mqRGtzgVewsaOZ5AScYwfm1n54Nhj41oFZxbQC/v0u1PkpIY/MSAeI6zqfPbBH5DPJGjEBFpDm7PnIsK5TUq8CrQ1zSSlL7Amu8ztNLlSisnZU4SojigruLJPaGssXJml1WXmmChDAY859rhNzLvstWDKNcyuxUp1jUg1R+f0jEUmycXRmHS5RBiJYLgg+3ESySi51DIT06c7EqmKAsmlqxuRn2RfCiB4aMYJJi9I6UlGz4949eVbHJ+EDBUToS4TV7OYQ5Xdlkk5s8S6oHAwkxGVDgtxxEf7LwCQBRWtNSIczFCLWYyZQbKhkYxH6ewf4+SinIy6tLwYi4szxkaLodPh9tsv43sJzOnVj7AYnJCNLRgKPlPTQ46CaVlMbJ1sbQPfcektRAJ3SnjqM7IdLNsilq4ynVxdsS28FJR1+q0F9ZU1rPmEeEwnIbscuxYT/xmJYoTxvE13GkOXA0Yj2N05oSB4XFu6LMwR4wKFeIrMvZcZugqzICBaXuLcTeC7IodnLtVshrhW4eHBR1SKKrdrK+TTRWRB46R3yT5r5oCI1SOXhY7RQZCyuJqDFlcwDJvMvXtU4jKd/WP6xjGzRR8/SCLFTLxFCiVzlWbm7ywRVzQUeYJm6USDBdLMIRkrU1spIVt9ilWd151tbm+9xGJksv3uBrEXjyh2zzHGl52cBk6HeirGwo1gtVsktArGaRtJyBEsokTkNHGpwHDcQQ5Vios5WryMEncZWyM8LgeT+DGJSSxLNZljEYaowZzRZMhsatNY2kS+uGAQtjjfN4iGAvFgRmXzZWa2S7F+2cL9/7G1ynVUpYqkeOhpi45soSoTakvLTG2LmTWk8mqCV2/dZnDRx3s6orp2m4vRQ4bBVT+CtDRGkENq1QLHvT6JpS0ksYoYERHjcYR4EnMwIpBEmmaLdr9Hys1QXl4isEaI2uXezps2YjROr6uRFPIoOZtossrmtRQIKlLSYjC1GPV9PKXAYKJRSKdomR6GHlCRftrl4ZcECCY5kYunErdX6uSlCHOjzy+9/TP87vt/wlLq60xHLZ6fPeXR+09oRarsyyLzhcTRTpPcUoKZe+l4lmvBZMbQWSALCmoxTRDaSFEbQVXxNIdYTGUcnlGpL0PCR3RbHO99QKrq0mleIbmFjOdMGUkJUkW4sENEuYDvDFFdg1GYQFBqRGIxLK+DELVopHK0piNyK1fDVFunJ/hhltv33mHkSsSSp5wah0QXC5bv1ZBOd3jjlSrfffyciL5NTl4i3jd5540bfPajT5nalyeC5yk40RKtTou+4zOwQpLlWzRPRoSKh2nG6VdqtA2H5oFPMZUmXU9TzS/TtiCfv+xroIpD4hkVN6qTrW6DZNLsNnEdiY4gkrZN2lOBhZIkaZwjDM65vrxOVBzTMUcko1caiTCSYLctkjaabEkaK7VrvPvqK/yTj3+EK0WIaUnOLj4irVeImy38eJJmt4uuxXg+l8lELh0miIT0Rj66CEros57XCbUS9niKEMshignOmlMEVybl9HGGJwyjGgvfpHh7Ce9z2XNFX8KpZ/CsKMbslMMnnxB1YohuFDnZZjlTZrWRxbQUTgcKcqrE+ciisrVGSJxn4+9/sTete44cS/Okd8Y3b28QtQJk2+WfNf+CTCLCYjQmqdi892If001TX1rDml5Qi6rs7l4dBLF8CgmH0cwnmygR0XXaUhl7ZjHpHyElqqh6nGrlBkJ0hGQ4rG9VSAoSgVXCmH4u4HI8huM+mRuvYrY7ZMQiH+zsYA/HrK81WErFSU9HxJfyOHKV9sAl4wgkfY/jvS6hJ/HWjX+5D34pgGA8m5NrxJlNL9jYvMHqxKT38T53r73J7v33UAMdWeiRWXisrb9OIhfl9350n+W/8QaKLhLGAmg+ILTmmI6NqAr8/M/dZu9sj4tOi52LfYp3XkPSKshpl1VdIBZJ4U9njOd9qkqacXOHpHrVzkkSZebBgoUU0DGn9G2daDyFGLnOqRGQKSwxM+dky0WMNphTg244oqxLiMOrQSmFtSJ6pUR9OUPv8RFd54yf+dYKe2efcMgjUssxlPUES4rOeXuIUBeJji9QPJ/6uo/x+Vj0RPUaGDOmvRZSosLo5BCldo33jue4EZmNZBU/s8qz4XMipVdpqjPO3BRWawddTrM7u2x5ZphzFl4ELZ3ANBecDvscs0BJVTmZjXn6rIsix6hkk8hTmZRYIGII5DyTjBBB40p9NxZkEo0UxViUcrmOJMx59PBDaulNHvQ+o/zmK6gvJNarOt6ZRGd2Qeru6zyyn6FtrqIoMfjuPyZwfRLJAka7Sb1WxJ9M0RYxtnJlZn0DazBiWxcZDsdYswGRhISJjBePE/gynvB5lU99iXQ6S2FZYXi2YKuxwslhk9lwymR+zrWv3SGYWJyf9Ihn8/TtC0xVIlYucWr4BMtLX+xtoYskYgq3Vm/w3v4DhovHmNqM58EYaSGwuZ3EshYo6RJPf/SC8o3bLLcsPCWBHLkKw+OSirXwSEQd3FBg9OIhS9VtPvnRIZHGTcopld29E9oRgYwq487nbFbm+CpU0zbNxWXaI6by1KMjanqC7754Cv6A+NIyglYiUdMJMgt07QZPD/vMjSHHLYONV16iEasx86dY/lVK95PsSwEEt17/Kme9PjPT5Y9PTijtdXn3xpscHT5CETNYdsh4IPNr3/hVvvPwDPPhlLWXXyK5nEYSLVbSKf7iL/4QYzzDFGVGwoC/2ntBdSNDoaTRbynIt0qUtWVmrR5Ne4rnjShmEqw0avSnsJhP2D+//8UzxQMPWxUJfQ3XX8ENFwh6naiyRbl4jb39HZAifP+TR2yVk8S1KtHuCxTRRI1enQhBT0WuKkybe2yVRfSla+yMP6TvtKjV5iREkz96/yHR4DqFpZfY3X1IVpQZjppU1CJT5ZLkScoBvjNg/cYq93dbqFkVKWri6Q5rK7dZiScxBQ88h5UbWbbSMR7++Q94906ZkdMlH7uMUmr5FCPT5bgzRCzXWJQ3iCpRtGyVrGIQjwS0hz32JxNuLr+Kw4KJ6pDqz4goPonYVR3Fy2/f4sX5mP5xl9jbNZRWn3wQZRiz0ZMFnnZh2U1z+/pX+Pan36GwcoM+Fun1ChE/wo18Gv4naJQUdNUkr+fZWGlw/FdHCJZLOOxxLdXg0XmPpOzjeAFrq8ucHn5Car2ClorSnXQoZi+jpnkAnU6b+TxGRCrRnHjI8gqOsMM33/o6Z7s7bNRL/Nu/8Iv81ekLkvM6ZhigpSwsLHrtq5bfxiyJNuniReMoiSTHIxOvOOXaq1WmXp9BCIMLA48NqhubnE4MCl6GQr6BPrpKMZ1pm6RqMnUhk6mhRVMM3Sl+vUKQX6Jtz+jrKkcPH/O3f/Vt4oHM0We73GykMXpdEpnLWpPNdA7VkJh89gm3G3n8eI3v/PAHSIUMi3aM7UKJC9K86I1ISS6leo6TjkEll6S+dZfZsPdTffBLAQRD26flQ2GlhLrTwa/XCFM6cl/D65to6KxUX8caitx96Q6uavNUmbB7sU95q0I5dingGZ82kTNlEvE6bqVBcTPJzHc4uNinIEgcB20m0RHl1WUalJg7EzbLS8z6FpGYjO0cfPFMWi4ktGLk5SxH84Di0svIegNnovN4r0clW2FoTbizdgfBPqVWaHCtnicVNMkmrkZn9Y9bBDGLg4M5m/fK5BURb3Yp6426FgtLJuc0ODlZcLj7CbrwMkp6FZEUMzFBdv1y5PfxeEgu7hD391laLjFq2ah+wPUyJDnlpfodBDGge79FTNKJqTpN44z9rss7b99joV9OMRZicZLxKE+ObUaHFk4yRreUxuvN8ZQ051OPNAob6zeQZRE9cElIUC1VmOx9gjC6qjUQ0xH0cI133lnG6mZ57doqo0KP7z/8kK2VDaTyBun8HX77D79HOVkiiPb57PEYvZhl6+Uq6c8VeCPDQK5H6A/HhE0fUU/QPjhlMDL4y+Z3SNUanFtTiuU45/IIL6IQy8UZOXMy1QLm5PInb7ddSqsbbG2liUcl9naPcAdj8tkY7//Vn3Ajn+bDUYvHu338YozccpXObMjue/uc90bUlwtf7E0OJAp5mU+Pd9n+pXWMzSWstZe4yM1IZdcpFRPMjueExwr5dIHCoIxvhIwnIr3R1XyEaDJB6GtIGFgxDTlaJJVtUEpNGbsqajZHRnBZ+cUMthjgGD6VRo5aNcpGWqFrX/7bxuAA+zzgcG+Hxq13CLUId77+JmKmQPNiwM4pHB/sUJETJJINTGOKI6TREml845yVtWs/1Qe/FECQKKWRvRETt4cUF5C6IU+eH7AVizFXZ3TPOsTlKJFIjEK9QLIs4WnnTI894pEMeuQy/zUHBpWMSrzcwIvGERYS9WyKTm2JZFTBnE0opyOkJB1FC5kObZq9CSmlRGi65MpXL8uau0SVPI7ic21jk3Y0w2S4IJbKUE6pFCIeek5k50GTG0tpBkfPcNcjdMYzbMn6Yp3JwiceKETiVeKpIp39U6JLCY6bZyw0CdGOohghqXSZ0VkfDRUt6hGEMrlQo3fweat22SSlxxgNOqy+lKAfSCwkg9vlJVYb6yQll7I0Y3wrQav9gr4hsRSPUSgoyPQZ9J9d7ss1sWyPTstGrORQtCRzV6M1nVFfKTPoNinmdFzHI6YlmbsyJ6MJi/4IrzuhJP7YfMhaGleHiC4xGwwZRUMGvT7Xiw163SGu0eHMWxBz4qQWIiVVYaUSZRQtkS+ukhUvdWSlfIJFYOMvXJqdPnk1Sdsc4PQ6IGqcHXyGi6+htAAAIABJREFUkk0jWz6yE5JYzWFHbNrDEaqaRYhdKktDLeTmepnZ+JTVWImpLONmchjTEXagM3IitFo90mvXKKcrTGcOaa1IdD2FpqjMgytu57A1QTvzaKyv4c7OEQWPmK6hxQQsOSRXqHL+/FPWU/eQDInRhUXcjDPvBVjdq3dEaJHLpAgmEtlEgY4sYboe6coSEU8huqTyMzeLNF88R5uPWDgJZLPLRdsgLs4IuORRFDSyFR1Nu0XPh6gTxfZdpKSGolcxfJfZbEw5nQAxi2tYTO0Rs7SJ5/foz3uw9S/3wS8FELiCjJuVmY1nSCOP7e0oDV0mcWzQ+vNP2ajFmTQvuPXVX+ZF+AGzSYyUHLLotNn3+3jBpcR03Dli9fYNCtUUbd+gtX/EQImwXNHRFIuONyPW8ekHLhd6BW2Rw7MiICw4b49ZBFcCx88OD/ja33ydfm9Of2yTkGOIvkncOuW0f0FvpuLIIxb4yLEqSkGg686oNxos+hdfrFO//hqNlIMcD5iYNsYkSiESocKrlOJTPGPI0ivr/I+/+ylr8eu0mx5+dEYsHSMazjk5vszJg/4Yb7PK9eo2xnxCej7h3o27ZIZDZG0PbzpAmMIt2cZXBfSEif7yGgvZRo+XON4/AWDeb7J7MEZO3KU3snCCDsl6lZbrcLHznM7gAvPI4uZSlpi4ieDB/qf3sfQAyZqhildpTyVbwFV87OYQ3zzns8ePCQ2blZVNeg8OcRjj2h5fv7dMezLA6WX42u0lpskiTz/5ACt2KemW/BkDx2ChCfRGI5L1DNKGwNxacHa6h2PNyYh1Msk6iXqCIWOCIEOikGc6GrFZuczJpViag+Fz/t2fe4Xo3Ga0N+Ck3cQeHfPDp11qisO84DJ49Iw3c0UUzimv1cmXq0SyWzw+vAqfJ67N0zONX3tN5Pfe7/Az/8FbvNc5pKJLPN9/yscvekj6GrYUopoyhjEnZoTkAou1azl4/3Kd2aBHqZgmHy3Q9wxM73JGQq2q8OD8GOs4yah3RmiMSIoK1sV91IhPTDbZLhb54Nll+/jjkx6K2EO0NZRCnpmhkkxluXgx5sIIiUgZ6vWbjHwR2c2ylNHQ/Av61gHbeYfHj68iuZ9kXwogeHbwmFnKJJcvUlA8LCXgzV/8FU7+/AGLzpTuvIVi+Ih5iWs1uJiauE2QfQ19OKdjX5bqJjNJdn/4PUaLgORSg1q+Qtx38E+GrFxbonU6Z6EKzO0pTn/BylqBzOYNzs+65NMRQvHqJF8pVPjg48c8O78grlYxdYn5vEvQmxLkE4Suz8VgxHI1S0KNMcLj8ZMLrMSCRvKqRU025qNIItVUnpPREWtKih/88CO+8s2/QezkUyaDDT747vv8YvUNvv/gBVNRZLZZIJHVEDyVG3fW+Oe/A5VyiWp1mwf7D3GsgLmY4EnzlH/nzgqji3O6C4OIIrJz3Odv/e3f4PHjH2GYHjEddo8myFwWVDUSMkGjjmMYnI0GIK0wOD8iIgVs31gjmdeQ5iZm+5z++H002yNptzgfjvn6jRWuxX+sMCe0KU1m3NjIcBSeEpvlWcxCdp+c8ujRAds3EqRElc54h5gi8fLqFol6jr3ekH5WZWpe6jaScoicTHMWDUkICqcRKLxzm+07N1CPz7nonlHUK/SsKeXb63B+APM2qphkPDdYfF4HdXi6oFrJsNc8Ia9H6AmQfmuDwz+bIWsTnu48IuxkiJcyDI8P2LqeY7Fw6RgHaHodUbzam5eMEE+oPHlySCwi8fw7HxOsNCilp8zHKmdHIffu5Hjw7U8xd6MogyiR5DZF1WE4vNKj5GIpPEumac44NCZczHzC+AmhOqCWzIBq88njT4kvRtQrFUxvSj6XoB5fwphP8E8fASAn4hSKEmk7xU57iOnMGE9dotE8t7MxJiOd8wcvqCwv03/+CUIuZPUlkWJK42zYwTZaP9UHvxRAcK1apm/0UE0BPVnm3utb/ODwKflShlf/w3+Pf/HH/4ismKCJ8H+3dyc/kpxnfse/sWREZGTkvmdW1trVVb1vXESKpERZMxgbxhgYe3zwwYBhXwa+Gj4YBnzy2fDZlwEMHzwYzGAsjDUaSaORJVFkk2yyu6uqu/Yl932JXCMzInwomkXDIx3lJhSfP+BFVAfy1+/yxPMiCEGKQoej45cMZiLC1jqLyeUPT47FGVYHzCYWxcNdkott8ksxDk+bJFWRa7bB0WmVSGoVeWOT/nhA6+SYSbmG6ffh919t8lSq57ibQXLpMHo0Qa1bQ1fn7O0+Jiiu0nYXhJNxAhmVl80iGXVBx24zGveZh1e/HCeRMQiJQ2y5h1ScUWy84O21N9g2c9gnDmKpTu48xs+fH/Hg/VuEEgGejMv0pyNSbhz/F2fkltWlUe5Q6Xa5f+suHw9rZAJRPj8rM6iPaV602N0/ZPn1TX689wzZ5yOUnNGf+bmW0nDcy02+/rzPQpiSXr/JZmaZuS/Gk2INLREE5xi/L0xX7GImJVK+JFb7lNdXM3T7Mkv6DNe5OmJNaXNQZwiSi6Fa9NtTnjz+gL3DALffeYOpuKBWfUmCVSqjEYMXn/KelEMwlkglw4T6lz+81UiEg14DZSyQSgTp+kXI6wgjgTvvZnik3mHe8+MM2oiuSNBZZdSaMB/NSGRTSOHLdXQooKELE6yhxNSvIOgCcSPLjaULZq0KP3raJ2ylWXebTD96xti5htj2od64QyLh8GHxqrPQlBH1ypSF5CKkRPTZMpOGgNG7z6PYTf5BfgnN6tJqhInGIuQSkPfHMLoTur2rWZNV+jkd6xrzYIRCPMPIGRAMOli1zxgOEqiGwes3C4zbEImFWcu+TVjXcM4PyKdTjL9oqBqWOsTUOLgjYr4pfkmjN3RYzWqIQ4GLT3d4UFhGNCtE8j5iEYVe8SOsThfXckgYX4NTg2Rc4fiwTqfdRnPAHxvwzrd/n2d/+wR1XmcSECkbIY7SWcYn5wzbfRwzwEooRO3iCMm57FD0e99+lx998AKfkeTOW48YnB2w0BL4kyI7lQmCkmbgk5Fd2AzpzAWXTqvGbDYFYU7QuDoj/8a96zzrNVm+u83z3XPEuYM97fA7//gt9homxsJHMpbg9s11ZpMy0ixMRL2J066RCF1tFlZqDYIbGfRgkoQhsLR6l3JpwNHzEv1zHam7xOFFids3NU4eX7D9KMj29SjDdoOl/B3O4pfT5wfrfmaFPg8jm5RrFVLhANNBk098EqKgcjzT+Xg4418UtvmfH3xEJiMT80d453qGaqnNsH0CQNAZocYD2Hab5extTos1Nld9dDonhKI5Pjv9EL8W4xvXtmkXnyNEHIyQgDD1YaguG4GrL+sW52Wwe/ztn38ffTrCH03zj/7gXUb/Y4/UNYdo/AY9M8agW8e9GPPx7jM2gt9C3ghQ2z0h7LtslhHQZbJimok1plQekHyQw/ZpzJw2qYRMWAlQG/UIJ3wMG22iURGrIVFIZ3GmXbQv7qOoC0OGmszPnxwQD8t8e20btdFHTAVpjGy+s/kG81Ca83aXt7/7Pts3DITpmM58znSvhTW+mhHGxDC3Xkvik0a0h020IVjKhOVpFCmQxR0tGO3t8t0bd/j0ZyWOelXsLQ2nJ9KdXQXKrUKUkV9mlk7y+OUx0kRg2jdRc2GuZRM8vSiRzofZSKwQCmjMewOmjsocH0flU2qlIgBmtUQmk2Bl+Salsx1sXwBDcTGrZUq7HSamzlG1yXC8z8pqnGGnTOH1JfZ2DrgVDTP8Sou5v8srEQTRiEg+HSAVdem5I4yYj8/Of0ggbrOY9VCvdZDFNDuHj3nzwTXEiooyntMYtRGHoEcvS3pX9QjxgEZXcalXhvRLXWRHQM/eIKRNGQ9bbK9FSSxfp80McVSlbSqsrcQZnp/w5On+l890cbjD0vY1PvrJ95CCca6vblC+cDDbF7y3ucVPPzohEPPTOPqARxtL1OsVFNVG8A+JulebRWa9y77YJNg0SIeu0xn6KJc6BI0wwkJnsRjz8M0bVDpFHt3cJrKUpjWpIjgqp7uHDLqXy55IAKZ+g/bohGbvlLtb36barXKwU0Kwgtz51muUphM6/SH3VnLks36qxRJnx/tkBYfw7PIT217XonSwwyiZ5+QvW8SXVvHLYYLOnKPPPuFGJkalXqH8eJ/l5TQBwYLpiExoDmYFw39VPt2ad2m+2OP6jRv8+Oc/Zis4pD6dcfONMAIt6rMuohMgHtdZuvkI/fGQ7P07PH72DFPXqBYvp6uNwZBiacx4rjKxXEYzGPQvmNQqFH9sE4vGsKciQq9PJBSmY85wFhZnRzXCfptc/LJ8etirIgv3WcsOULHp900G51WOdw7ot5uIPp1m85z777yOoY1pWXAtcx0kH6HENkblqjHr5lqMxy8+I5Hf5mZik/3jfSJTlZ2dBpkMRNUInYqPcCbKyqafcSXOyUWJqJQg8JUS88moiCrAxe6IerNNZnuD4nmJYX1OT5aR6230/EP8vQq6kkXyWRwdHPBgO0Kw2EA1Lseyxy6DxowngzpCdJOZaRFQJYyoQbF9hu6foWt+0sk0kjhBy2/T6fdYu3YXzqoorV+/R/BKfH34xsNr6EqHlajIdsbBHJ8zsY4RjDbVxR5SWGP9moZQGNCVyhD2YW+5DANDVH+VVO5yc87Oxrj3nbe4s75Ou3SMJCfYPxrx8vEnLPCTTq4ST2YQ7DHuwSmzqULz8Iy9Dz8FJUw8dtXO+r3X72OPBjy8vcrWUgBpNOX+rYcUtCxmvc1761m0Tpu8OyblNEgoIqGBiT0c0v/KjTlS2KawmcOSRdp6l0H/gocPVxkpU0LLIvFHMrFEnzfev4uR0lDlCqngjNSSQXfeYit1eY9A1DdAn5+yIot8962b+J0yMjLvfPMdEpqPUb+Cz6pQG5yD2sNnVdhI6tBvcLb3Kb3W5Wah4vNz59YNrG6FUGhG3LDBHKAtBCKuTD6U4O/fWeZGJsbbqyG+cSNBTDAJ2g0ce8HQvZrtPDv8gNbU5JP9T9k/2WWckPllfR+SbdqxCz5t7DCLCJyER5w4TQIPVH5w/pQds8fYPGEWuqyR6FdsOuUJru1SyKZQkZnV+sgEmA41dDdL/aTHcKxzeNBmMQwhKQa+gIQzhZcvL2c7Z/02p8U+vkmAu+mH3L6xjF9xCScUHry/hR01UQohcht+DjtFcmtZkvkCM59Kqdfi4uzgy78tHbbZWllnYjWQnQZLfsgYYaLtHu6LfVrllyQMhe1UlhurG7QbR+iSgq7N2Mhd3f3wYDNDIe6wdTfIW4+yFIQBK+E11rLrJPUEb61nqH7+MaWLC8rHT2hf1FlfkakfvsCW55jq5WwnnArjC+vUB2U65jMicgdR6NJs7LO2qbB1M8jvvL9OITlhQo9GrYIqjClEDBShxcL8GuwRPP3gr3EtB3tuEvQtIOjnrNZiqg/wyRbnww5ia0REkIgIMsF0CCdyjfPKh6xFZabO5fo3nrhOIKHxo49/QdAIkfXFmcejCPKUSqnCWb2OGguy9/yU5ZyK4Q5pVhqsPLhLp36CIF51KDJ7E+5lN+g5FmN3gRGRuKgVyctRtKDOzBxzt5CiP2syqVWZt1wq9TohNUzYSH05TrN/ijXsoogybm+KX0vT6o2RZxN2W3tsFUKMnREpQ2ck11A1l1GvhzBfYFkmz+tfdBZSRcTxFAEZZ2LSbp/w7ZuvY3ZLLD1UefZshwd5i0IhSGBcIqGGcWcOgbhMKr+JaM3gz8AmijXX0Bw/wkWbueCnUe5RHg7R3CBdq8+cKYpkUaFLxPATVTQG/RbYEs706mSl0nBJqAE67RZTYcRHlQaDXh3SU1Y2DXrVPgfiDtNih5GocbuwjCD3GDp9FFHGml3W9ndbPcZjUGSX7rCPMLGYjEXmrsD969t0in0Cjk7nos3GaoHe0CYTTtDsTjF8c0L6F2XY9UMM5QGOnKE6GNAc9xHjKr3ynPFkRjekIM4ljgdjRDHET352hKCfk9m4gxARmSpXjUmEeABDNHlTzhMVIrQrY6xGm+rCZjQZ4ztO4bQOOV6uItou7niKMYXtxAruV/5/jUTTTMZDso6PaDLAQJjwe9++SfWgh0/S+MWTXW6HI9iTNubZBC084LDcxz+HcHjG9eA6UKJWf8rYbaEbaRxBZjGTUGwfAXdGLC7huhJnT/4CkwW6PcYI+rA6M0Zzl8PjHfyLr8GpwepyFNe/QJ45TAQTIQ1r4QlzYU7EcAh1bTIhg15rgBJsE9RdSoeH3CnMsEY26dzl8dHLozZ+I4bhj6DFVhi0x4w6Q1KKhiu47Jb66J06gmtxul/C0SXsocVRvYOoK2ju1TrqvDZEKA7ouwtGQDYdY2Za+FU/Vn+EpmsM2mXGfZNZUGDQNhFHU2Z9h7J9dXyoSSBWNKZ+HxPdoJ1I4RdUhOYYwSdgShOelkckpgeE1DkXThHmDrn1NMKkgu+L8llzajJwHeY+jV67iz6YEZh1uCjVsMeQMywqvRZW8zMiahCfA/bCJKEJmOYEXbrcLJoMZ4wnNtFgnIUSoHPaRJ7ZhMYDfAsLQbYRjBARLcCi3mcyGuGTbPwO6HKA1lc2wt5/5z1axX3i1zdIb/Yx5Q5GykUI9QmkClxfaxKPa6jra4xLhwTWbNxyh3uPVCZTH7kv7qNomG0C/iBYExLBAOPOEHEskY5HcNoVopMF2ZCfnuvH7leJ2n5GzQ4Bu4/sznBmlwU89978BoWVNDFdxhy2CS0sHMdHuT+kfVGm2GiRS2mI/iDqaoSte6/x2clzegGZUadPKHtVUBSNFLh26y1M06RjmgTbfZKOi9UqgRuiVa3g2AJ6w0YyXJY236BzVGakhVh85Rhyd+cxrpRgrkMkW2A8tBkel6ifvsSQDL65vcGi0+VkviDud7B6ZXz9CeKsxdBJMjUvx0obPiaTJhE1iR0MM3EhG0gRFiSciYjZ6eNEXBaNCYWwiuSzYTJGHI9Yi+qMp1cnIn8Xr0ORx/NbwutQ5PF4fq1XYmnwr/7oPxE3JBq9Fh3LR8BIsZGLYnbnBAIauhqgdL6PFNDwu1OUoEz9osHK5gZBdU7MX+ef/+t/x3uP/ikRe0pIFUjmYoTDK7iSjhYy0BUFZzSj33GxFBesCYJVRFMCVE5fMOkrYLj88eM/BeAvv/dfuTivoIQFtPAW5dYRmdwW+y93yIWzBKISzVqFgeNDUQKElRFnu08prERZEnT+8I/+IwD//o/+A2N7iqwZCIKBMy4h+CQSfp1oyuDjp58TWLmGM1FQRxax1Q20SAh3NKB6csLW+i3+5b/9J/zpf/ldJg2J6dxi2FCI+HUc7TaVgUlEUTgvfQyTJRJrGdqdc9YzYdRsiPHhOapq0Xdf8G/+8/6vew2e32KvRBCo/jCWbRMMbRDVZSzXQQ9HkYUZ8/GU+XiKT5JYXbtOr3KGJIOqhVFUH4PuCEW+nNhIkWtoswrCqIliq/gDfgQxhC3pHB2V0X0+REkhqgcIJrPYA5nWqE44lUOJ+pDsqy/rZHHKvFPFsWT6DUAVsCYLapUWuu2nP5cZuxLbd+/y9LMddMElFosyHoxIFq5uQ25PexjuCDGsINgjTEkjaEQIhESEUIzYyjJzVcHsTYmkU/iN0GXrcmlOsVgmHb1ctxbrAgvbxBBDWD6NseVDEG1enpwT1v3YjsIiEKV6fMKdXIp4qEDQUNgTp8ijDv6Fhsfzq7wSSwN/JosTTmKpMlEjSDamExctppMBwZmJr3FKpFUnMKgTtUZERYl3H2zhm/nQ9ShS8LKPwNK1+6RX3iK1tIEUWsV2XERlQfn8BCGg8by6xw8/+4DWoslwUUbQQHZGNMwZspwEfenLZ5rLPuZanF5boH58Ql5conRYIagk6de79Co2mrJB8aCN3W4h95vM6i0UyyL8lQtOTHPBzCcy7FQxcRlHdLrWiGb9gtZwSnbzNpNmh6RfIxeXsTov0Fp7ZNwZoXCQSOTy68N2W+Vw38Yc3SBixDHdBU1rTFLWUEUdySggyyapWAxXkjhozvjRz14g68sMZhJzaQmP51d5JWYEg84AXyxDPmSQDcGkVsW2HO76g7iCiKhHcRMqoiuRyC2DDi/3itiSi6T7oHd51mqMF2gipJZvEom4/PlP/oZ8OMDq5hbqisaLoY9wPsrp9ARZVTEFg1g+zZ31HK2m+H+d/08VGVcXmE0EBh2T45dPmQeS3L//DZ789Dmvv/keY9vk8Yd/w5piIzFlu7CNptr4tKsd2s1sEl2dMpl3uXs/yMEgQOWghRXfYqIE6Y5F3NwNxu6C88UQazbAGY4QSl0G/T7l1uVHJ4xEMlKOp/t1lhILCsEAoZxF0lhiMgNF6/L5hztsLF9nUJ8wC4RQNIWiWSIXzKEo3ozA86u9EkEQCwSQHIvRoMt5t8l6eplxa0p/NkZq7nLrxl1YGEziWYL5VYTxCFMQ+PjEpDnvEf6iI1AiEANXQ5abOJLNW2kDfwxqrRf0HJXx4gjBge5Io6wFifldloIJZCWCo+kE7asfy8IyaY6LbGzkWFLyjBc5BD3FeFzi/v0tZuXPGdkTcrLCsHuMNW1Qj1R4+OZtqq2jL8eJixqV5iFhq0/p8ZTY7W2OUxKmkmKtkMPvd+i2ByziWXq732dze5np509IBHyEHIeV3AYASS1Gt3POo8IjPtr7JVZuyLD0jOsxH+OpRPm4iBKagBKiPepQq+7y5v136Q0sJoshczWGx/OrvBJB8KRyjub2WUxEklEdPelj0y+gBmwUY5nD8ie89fDbmJLFSeWUwWDBQa3BSa1IT/ERWL/8MONluU4+umAzNCVo6JyHHfbrJRbhCOXTJoYfYuqCIXOO+sdEK2Wu2S6pUJTDozN8savv0bVQl621BL1ahUAiThaVhjknNlNptCv4xzXc+YjpoIlPs6kNZ6wklihOG9zLX+0R+KU+OUniqLng/s119MQS8mBG9o1vIkRjWJSIhmL0ekekN7awxiZL8QynT3eJyzrx2GWV2g8/OeReYpm1zBIjX5bq8R4zaYabVBBnU8KRAUZTZL9bJJ1P4abiHJWrRFWNXmeMEe7/Zl+q52vlldgjOKi+4KB6RCxq8/rrWyiTGbHlMJ3OLr3yR6waNqXTj8lER5jTU4ZCi9L5EybdKpbZoVK5LJZpWzaJTBQ1EeLp2QEV/PTUEB27Rz/YIripYodHSHqdaFxmbSnKZy+fUC4/Q7BlhK/0I4j4ReadEr6ojZELUR7UWLRrfPC9H3Dxw5/iExNM2iqBZJawYnH3wTa5e6vc2gizkr+aWbRclW7/kHywyaePv082rpJZH/LTp3/F8/YBMyOG5lT41ts32bgWIjY+RWp+wnvXMyRSATT/ZZXi+48eEBVEFt3PWdEVgst+ghsp7PUHWOtxhNdWKN5bx1q/wcY33yKyHOdlZUylYtN3RMaSjsfzq7wSM4JsIs83CynM1meozQpb6xHExmNiWov7927S6h4ydiMcN4s8uHeTjuUi6G/x4bPPOGmAGLi8htxeqJyUakhCAykwRRx3CQVNhtKIf/Z796hpU8Kmn85Jh0Z5yng6IZcpsHXnNtaLEX3r6jvy2eiCa99awpnYlEpgzXQOLmro8yCiFeDiWZfBxCIaFtFXXye0atHq7RKRZc57V4FihbJc336IWHyBo8InOz9GX33A8u0Nyt06L6xz8oNzTnonvLmdomrO0XWR8/4x6cINSvXLGnF/z+TovEF24xpP9j9m5fXrhN/OMAuEiSZvcGGXcJ+PKEjXGZhQHHRRBnDmdrh1q4CvVfrNvlTP18orEQS+uUS3t8/d5QLfeU3EaY8ZxVSKx032jn303SlTqct5zea2dkHYSHDtwTaBeALtRY/+7HKXXqOKPRVxB0Ny1/OEVhLIgRmfn++SCUvMXJmQJpC7t8Wh+YR2p0OocIt2f0F2bQvrpHj1TIE5tltiFghzZztFzk2iz1XshUQgqhJbU+hPfCjrWbruISEN1OU0+BYcHz37cpxhb0TVPyYdVsnbRT77dMTta29z/Fd/wuNym5CukWgWee1uCvM0g7B/Bv0J8mLGcjjEpPdF12BFoWsq/OJnv6AdGPNsZ8Lfu7uBVYgTDLlYlTpDycLdEKiVFgxmQZpKiUCrRFS0EAVvs9Dzq70SQTARgvjjE5RrCbRwhr9++jM0PchQjWJWm8z1BYuEhDlzQDbozcas6Do1xSa2vgyty3X005dDhg9DiL0Ahl7AEC7oLmzCmWVOj08xtBCaFqTeVbGGCZbvX2do5/jBizPMdpXKWePLZ0pn0nx6/IJgCI7LF1QaE64/fINzq0Hnose0J5Neu83UbhDPghIKMZuYRGNhtFEA+B4AvnkIUV6hHtJJppZp/q9TfvS9H2GKYURb4t13f5+Tiwa5dYmcIrJ/NCCf0pl2R3z4+QnRxOXf9unRMbFrI7S+zmmpTHb9Jr1GmWx+hjUfI3UnFAIGFztNfvnHf0MytMwsNOFe2sD1TfHlA//Pv7vH83+8EkEguxoj20cwmOSTwZwj1yEwGJMIxemMWowXCt29JomlCM9/8gO0YIZKt8LS7ftYxQ6755e3+BgyrK+soLtNPtptotomhZjA8sYmHdNCOjpn0JeRhQlqRSca8lOujgkmb2FIJsOrlv1kbJMVQ6NS7bBfq+EPr9DSJojLMjWzhhFcJpQTUc02PXNB58Uh0eCEaHadzEr0y3HWCzKlgU37sEEsv428bVM1dVLLK7Snexw/O+P2rTxzzeDk/Alrm3cwmy9ZKsRJ9SIc7F9O6XPrAVovG4QVm+trATR1RHOvRD6tk3At1mLLdAZNHj/7kEJc5d5GmvPOMbe3lzj/6JiVjSQez6/ySgRBe1FHUHQ+fXFB0B3yu4/e4OzzMwKdlyRCac4bJxxUJHr1Oq99602yiQi5qIEvKLISlPmzF58AICTC9MUw+WiSQnC85lg2AAAGvElEQVRG5WTCtD2k3D1jKZhi/3xAJpMl4Tg0AhaqEiFyO4lo3GLn8QFD46oNtR6IUPzZJ8jRW1xPheiqOlPBprBlMFfTlPsCp4sa+YhEt91lOScQQWZx3MBIXO3BXhx8hhvXiS5t8N//4q/Z/M4fsh4HyUiz9e42xd6QyouXZBMxBjOXhm6zmn+TwGJOp1lD0y5rJHr1IzB8PHrvH3J68jFqLAXjEmc/ekbSiLE7PyShGIifH3Br+RZ2e4dvfGOTZ89/yZu37pEuGL/Zl+r5WnklTg0GvQaiKqG4M2R7ztx2GU8m/PzzXeaOzOFFm7GkEE/kUTWD7shCmFq0T+pMhRErhQwA1kJiZsJHn7zguDKi3xxjzvxIlsJiJqHqS1iDCIKWw54uwBEQ3BClco2F5CMUD3/5TGdFE3wBWt0O1ckCJepDCMxYuAPciIQc8iHFZObiiFQmymKhsnBUJtaCsLH25TjtaotoNIHrUyg8+A6aT2U6AZ8o4gsaqI6PGCGcXofwVGQyHGGN5/RqTVRslpYuTw0mnRG5UIbj3pBhJ0ytMiA8MtgKxLFKA4SZTf/8nE6tjmWOUJ0kHXuOHk0yWgyol57+Zl+q52vllZgRjOU5K9sPeGDIGNqC4u4584WGFUuiqQvy8SB+xUB0oV5vEk6GaFkyS4XbCIMSunJZfRfVfazl1ngxOeX20hKGblE8LXNxcYaYCZOMJqjUBpzvlVi+sYwgpFksItT2d1lPLNPWryoCD1/UqR7O2HgjjqnbPDn/GGvQ4Lub73HjeobW3hHtvokqyyQLBpYtUawWcdsWa0Pzy3GUZYOgAaVOn7dv3cEf15hYfp6ft0jlNTbeusPhzwcsr9/A1+lSe/4BIUUgv5ZkMZWoXVyuV/IrKVR5iKIIxB6tkhFiDAImT/decH42QI91CKDwB/ffR4vlObYVIisxCnoYc/+CeDIDPMPj+bu8EkFgDV9SLTZ55+17TEdVqsMq1rzH2voSH5wdUe60yG8VGIf8pLIBIpEwpeGYhXlGq3rBYnZ5xBb2+7FHTZZid2iNk8wnXTpWH3XpLt1hj+NP21y/t0m9Z2POFPpWiNHYwhAiFLsLFDX45TPtP/2Eo4suNhKr31wlJS2omLBzsItPaFBtX9DqNrCSCUaVPtnlGzSLAxTN5S/+2598Oc5qRMFcmGihIIFIBFtecFQdsP7oLkHF4OT8kIcPrsHEYSAUSeXXCBgixf6Ift1k1LysmnznnfeYM0dQQ5jmlMrOMZIaIWqrGJkCo16Ye6sR6tUubXeG6JuiXMwwlDZTqUYosvobfaeer5dXIgjW8znSSwo2FhcXzwkGHXpjmec7J8T8CUR9Rl+YMG0OeOkEKba7BOM6/oUPK6ShLV1+mBMLBfHrBoV0AkSR+jSOrc0YtesIc5f0Zh5BTGIELSRfBktZh1iUkL9JvT5hPPnKDTWdJt/degNHCzJ7OWI7v06zViJ1PY9jwzuJZapzDcF0iMV12gf7BCUBrCl3N6+Kd3abXbYyaeJ+mfPiPpqqE4tuE5UTFI+PcUUH7DanxzUWXZfMUpimOUAzFF4+LZNwLptXHnzyfQLrt0Ao0h3oyMkNlG6DWadHo+uSyoX42dE5WzmdltliM5XH74elxDJzc0y9/et71nl+u70SQSAFXPae/y+m5c/pVo8IzBy6XYvisMnO6Uu65pDQeYit124Ts4oE48vs7R3w8vwUNRLG51w2XqlU2vjDXfoBB78cJBhMwkRBCur0Bi26PRVtqjIdxRGnCdZi1zjbO0MJZxm0XuKOr3oWxjKr9HpdFPKsLy/R6kmocxG7NUByfHRFB7+SYLkQxeyfsZHIMx5XaVXbNJWrTcegFaDfmKHIIu3JnPncZP3OGiO5RMCakwsLKD0fo1qfwGJO+8CiXjwkm1gjHUgxbl4uDQwthd7t0o9k6Va6BOIlqq0LRCuCi8BxacBytMBxq0TMl6bcGrPmi3Bc77GdXmNhD4GPf6Pv1fP14bUq83h+S3ityjwez6/lBYHH4/GCwOPxeEHg8XjwgsDj8eAFgcfjwQsCj8eDFwQejwcvCDweD14QeDwevCDweDx4QeDxePCCwOPx4AWBx+PBCwKPx4MXBB6PBy8IPB4Pr0iHIo/H8/+XNyPweDxeEHg8Hi8IPB4PXhB4PB68IPB4PHhB4PF48ILA4/HgBYHH48ELAo/HgxcEHo8HLwg8Hg9eEHg8Hrwg8Hg8eEHg8XjwgsDj8eAFgcfjwQsCj8eDFwQejwcvCDweD14QeDwevCDweDx4QeDxePCCwOPxAP8bLBMO3DW/LFEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the weights of the best network\n",
    "show_net_weights(best_net)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run on the test set\n",
    "When you are done experimenting, you should evaluate your final trained network on the test set; you should get above 48%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test accuracy:  0.507\n"
     ]
    }
   ],
   "source": [
    "test_acc = (best_net.predict(X_test) == y_test).mean()\n",
    "print('Test accuracy: ', test_acc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "**Inline Question**\n",
    "\n",
    "Now that you have trained a Neural Network classifier, you may find that your testing accuracy is much lower than the training accuracy. In what ways can we decrease this gap? Select all that apply.\n",
    "\n",
    "1. Train on a larger dataset.\n",
    "2. Add more hidden units.\n",
    "3. Increase the regularization strength.\n",
    "4. None of the above.\n",
    "\n",
    "$\\color{blue}{\\textit Your Answer:}$ 3\n",
    "\n",
    "$\\color{blue}{\\textit Your Explanation:}$ We have overfitting in trainset, add units or train on larger dataset can't impove performance.\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
